{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ***Introduction to Radar Using Python and MATLAB***\n",
    "## Andy Harrison - Copyright (C) 2019 Artech House\n",
    "<br/>\n",
    "\n",
    "# Matched Filter\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Referring to Section 8.3, the matched filter is an intrapulse compression technique commonly used in radar systems.  The matched filter is the optimal linear filter that maximizes the signal-to-noise ratio in the presence of additive random noise.  The term ***matched*** comes about as the filter impulse response is matched to the radar transmit signal.  These were first referred to as ***North filters***, as the concept first appeared in a report by North in 1943. \n",
    "\n",
    "Employing the frequency domain form of (Equation 8.22) allows the output of the matched filter to be written as (Equation 8.35)\n",
    "\n",
    "$$\n",
    "    s_o(t) = \\mathcal{F}^{-1}\\Big\\{ \\mathcal{F}\\{ h(t) \\} \\times \\mathcal{F}\\{ s_i(t) \\} \\Big\\},\n",
    "$$\n",
    "\n",
    "where $s_i(t)$ = matched filter input signal, $h(t)$ = matched filter impulse response, $s_0(t)$ = matched filter output.\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set the bandwidth (Hz), the pulsewidth (s), the target range (m) and the target radar cross section (m^2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "bandwidth = 30e6\n",
    "\n",
    "pulsewidth = 10e-6\n",
    "\n",
    "target_range = [10.0, 50.0, 100.0]\n",
    "\n",
    "target_rcs = [1.0, 3.0, 2.0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set the number of samples for matched filtering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "N = int(2 * bandwidth * pulsewidth) * 8"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set the window type (Kaiser, Blackman-Harris, Hanning, Hamming, or Rectangular)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "window_type = 'Hanning'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get the window coefficients using the routines from `scipy.signal.windows`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.signal.windows import hann, hamming, blackmanharris, kaiser \n",
    "\n",
    "from numpy import ones\n",
    "    \n",
    "    \n",
    "if window_type == 'Kaiser':\n",
    "\n",
    "    coefficients = kaiser(N, 6, True)\n",
    "\n",
    "elif window_type == 'Blackman-Harris':\n",
    "\n",
    "    coefficients = blackmanharris(N, True)\n",
    "\n",
    "elif window_type == 'Hanning':\n",
    "\n",
    "    coefficients = hann(N, True)\n",
    "\n",
    "elif window_type == 'Hamming':\n",
    "\n",
    "    coefficients = hamming(N, True)\n",
    "\n",
    "elif window_type == 'Rectangular':\n",
    "\n",
    "    coefficients = ones(N)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up the time vector (s) for the matched filter using the `linspace` routine from `scipy`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy import linspace\n",
    "\n",
    "t = linspace(-0.5 * pulsewidth, 0.5 * pulsewidth, N)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculate the baseband return signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy import zeros, sqrt, exp, conj\n",
    "\n",
    "from scipy.constants import pi, c\n",
    "\n",
    "\n",
    "s = zeros(N, dtype=complex)\n",
    "\n",
    "\n",
    "# Chirp slope\n",
    "\n",
    "alpha = 0.5 * bandwidth / pulsewidth\n",
    "\n",
    "\n",
    "\n",
    "# Loop over all the targets\n",
    "\n",
    "for r, rcs in zip(target_range, target_rcs):\n",
    "\n",
    "    s += sqrt(rcs) * exp(1j * 2.0 * pi * alpha * (t - 2.0 * r / c) ** 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Generate the transmitted signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "st = exp(1j * 2 * pi * alpha * t ** 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get the impulse reponse and perform the matched filtering using the `fftpack` routines from `scipy`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.fftpack import ifft, fft, fftshift\n",
    "\n",
    "Hf = fft(conj(st * coefficients))\n",
    "\n",
    "Si = fft(s)\n",
    "\n",
    "so = fftshift(ifft(Si * Hf))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up the range window for plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "range_window = linspace(-0.25 * c * pulsewidth, 0.25 * c * pulsewidth, N)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Display the results of matched filtering using the `matplotlib` routines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LQq4hVBsvXGpjvupitmpjvupitmpjvu6kfEFIRERERERElSlfEHo8yr9EV4tGo1Y3gUzEfNXFbNXGfNXFbNXGfN2J1RI5Wj6ft7oJZCLmqy5mqzbmqy5mqzbm607KF4TcVEZtPEBVbcxXXcxWbcxXXcxWbczXnZQvCImIiIiIiKgy5QtCriFUG+e6q435qovZqo35qovZqo35uhOrJXI0TglWG/NVF7NVG/NVF7NVG/N1J+ULQv5iqy2VSlndBDIR81UXs1Ub81UXs1Ub83Un5QtCIiIiIiIiqkz5gpBrCNUWiUSsbgKZiPmqi9mqjfmqi9mqjfm6E6slIiIiIiIil1K+IOQaQrUlk0mrm0AmYr7qYrZqY77qYrZqY77upHxBSERERERERJUpXxByDaHawuGw1U0gEzFfdTFbtTFfdTFbtTFfd2K1RI7Ggl9tzFddzFZtzFddzFZtzNedlE+dawjVlkgkrG4CmYj5qovZqo35qovZqo35upPyBSERERERERFVpnxByKFvtQWDQaubQCZivupitmpjvupitmpjvu7EaokczefzWd0EMhHzVRezVRvzVRezVRvzdSflC0KuIVQb57qrjfmqi9mqjfmqi9mqjfm6k/IFIREREREREVXmuIJQCNErhPiaECIhhDglhHjrGt/frqaRBQKBgNVNIBMxX3UxW7UxX3UxW7UxX3dy4kThfwKQBTAEYC+Abwkh9kkpD1T6Zm4qozZeuNTGfNXFbNXGfNXFbNXGfN3JUdWSECIK4C4A75FSxqWUPwbw3wB+rtrfKRQK7WoeWSAej1vdBDIR81UXs1Ub81UXs1Ub83UnRxWEALYDyEspD6/43D4Auy1qDxERERERkWM5bcpoDMDSqs8tAuhY+QkhxDsAvAMARkdHkU6nkc1mkc1mAQDRaBT5fB6ZTKb8cbFYRCqVAgBEIhEAQDKZBACEw2F4PJ7yzkvBYBA+n6/8cSAQQCAQKN9VCQQCCAaDiMfjkFLC7/cjGAwimUyiWCzC5/MhFAqVP/Z4PIhEIkin08jn8+WPM5kMcrkchBCIxWLIZDLl1xCLxfiaIhEUCgXMzMwo9ZpUzKnZ15RIJJR7TSrm1MxrSqVSSKfTSr0mFXNq9jXlcrnytVmV16RiTs28Jr3NKr0mFXNq9jVls1lkMhmlXpOKOTXzmmoRUsqa32AnQoirATwgpYys+NzvArhNSvmaSn/n2muvlU888US7mkhtlslkeIiqwpivupit2pivupit2pivuoQQT0gpr6v0NadNGT0MwCeE2Lbic3sAVNxQBuAaQtVxrrvamK+6mK3amK+6mK3amK87OaoglFImAPwngD8XQkSFEC8E8DoAn7O2ZWQVJ41wU+OYr7qYrdqYr7qYrdqYrzs5qiAs+TUAYQBTAL4I4J3VjpwAeA6h6vx+v9VNIBMxX3UxW7UxX3UxW7UxX3dy2qYykFLOAXh9vd/PcwjVxnnuamO+6mK2amO+6mK2amO+7qR8tcQ1hGrTd2ciNTFfdTFbtTFfdTFbtTFfd1K+ICS1FYtFq5tAJmK+6mK2amO+6mK2amO+7qR8Qcg1hGrz+Rw365kawHzVxWzVxnzVxWzVxnzdSfnUuYZQbaFQyOomkIlUznc+kcWTp+dxfjGNRCaPnkgAG3ojuGZjN4I+r9XNM53K2RLzVRmzVRvzdSflC0KuIVRbMpnkxUthquVbKEp869nz+OyDJ/Hk6XkUK+zuHfJ78NIdg/jFF23BtRt72t/INlEtW7oY81UXs1Ub83Un5QtCUhvnuqtNpXwfPDaDP/3afhyfSWDLQBT/+6Xb8OJt/djQE0E06MVCMofnJ5Zx/5FpfO2ps/j2sxO47fIBvP91V2BDb8Tq5htOpWzpUsxXXcxWbczXnVgQkqNxSrDaVMg3my/iL759EJ9+8CQ29UXwsZ+9Bi/fNQyP5+L1zR0hPzb0RnDHriH8/it24POPnMI//OAIXv6h+/D+11+BN1673qJXYA4VsqXqmK+6mK3amK87KV8Qer3qr8Vxs0hEvZETusDp+S4mc/jVf3sCDx2fxS+8cBN+/84dCAfWviZFgz6845ateNWVI/i9rzyDd39lHw5PLuMPXrEDXo8aG2U5PVuqjfmqi9mqjfm6k/K3ATj0rbZ0Om11E8hETs53Np7BT338QTxxah4fetMevPc1u+sqBlda3xPBZ3/xBvz8zRvxz/cdx+/9xz4UKi08dCAnZ0trY77qYrZqY77upPwIoZRqvHmiyvL5vNVNIBM5Nd/FVA4//8lHcWo2iU//wvV4wWX9TT+W3+vBn7/uCvTHgvj77x+GzyPwV2+46pIpp07j1GypPsxXXcxWbczXnZQvCEltnOuuNifmmysU8cuffRyHJ5fxLz9/XUvF4Eq/efs25AtF/OMPj2KkK4zfftl2Qx7XKk7MlurHfNXFbNXGfN1J+YKQawjVxrnuanNivu//5nN49MQc/uFNe3Hb5YOGPvZvv2w7zi2m8eG7j2D7UAdefdWIoY/fTk7MlurHfNXFbNXGfN1J+dsAXEOotkwmY3UTyEROy/crj4/jsw+dwjtu2YLXXz1q+OMLIfDBn7wC14x1491f2YejU3HDn6NdnJYtNYb5qovZqo35upPyBSHXEKotl8tZ3QQykZPyPTWbwHv/+wBu3tKH37/zctOeJ+jz4qM/ey1Cfg/e9eWnkM0786aXk7KlxjFfdTFbtTFfd1K+ICS1CeHsjTWoNqfkWyhK/O6/74PXI/B3P70HPq+5l9ahzhD+6q6rsP/sEj70g8OmPpdZnJItNYf5qovZqo35upPyBSHXEKotFotZ3QQykVPy/eSPT+DxU/N4/+uuwLrucFue887dw3jTdRvw8XuPYf/ZxbY8p5Gcki01h/mqi9mqjfm6k/IFIdcQqo1z3dXmhHzPL6bwoR8cxu07BvG6veva+tx//Oqd6I0G8Sdfe9Zx5xM6IVtqHvNVF7NVG/N1J+V3GeUaQrVls1mrm0AmckK+7//mcygUJd732t1tn2rTFfbjPT+xE7/1pafx+UdO4edv3tTW52+FE7Kl5jFfNUgpcWw6jqfHFzGxmEI2X4Rf5nDV5iFcv6kHkYDybyNdh33XndiTiYia9MDRGXz72Qn87su2Y0OvNVt1v3bPOvz74+P4u+8dxuv2jKIr4rekHUSkjuV0Dp97+BS+9Og4Ts8ly58XApASwI9Owe8VuGPnEH7pxZtx7cZe6xpLRC1TviDkGkK1ca672uycb7Eo8ZffOYjR7jB++ZYtlrVDCIE/ffUuvOof78c/3XMUf/yqnZa1pRF2zpZax3ydSUqJf398HH/x7UNYTOXwwsv68I5btuDmrX0Y7Q7D7/Vgan4Zh2czuPf5afzHE+P4zv4J3LFzEH/exjXUZB72XXdSviDkGkK1ZbNZhEIhq5tBJrFzvt989jz2n13C3//0HoT81t542jnSibuuWY9PP3ASP3fTRstGKxth52ypdczXeeYTWbzry0/j3sPTuGlLL/74VTtx1fruS74v6gdu3T6AW7cP4Hdfvh2fe/gUPvyDI3jZ39+Lv3njHrz6qpH2N54Mw77rTspvKsM1hGrjXHe12TXfbL6Iv/ve89gx3IHX7TX+APpm/O7Lt0MIOOYYCrtmS8Zgvs5yYiaBN3z0QTx0fBZ//rrd+MIv3VSxGAQuzjYa9OFXb92K7/32Ldgx0olf/8KT+PvvH+Z7Lwdj33Un5QtCIiKjfe2pMzg1m8Tv3Xk5vB57nNk00hXGz920EV9/+hxOzSasbg4ROcThyWXc9dEHsZjK4Yu/fCN+/uZN8DR4XdvQG8EXfvlG/PR16/GPdx/B+/77AItCIgdRviD0eJR/ia4WjUatbgKZyI755gtFfPSeY7hitBMv3TFodXMu8o5btsDrEfjIj45Z3ZQ12TFbMg7zdYZTswn87L8+Ap9H4KvvfEFdm8NUyzbo8+Kv77oKv/SizfjMQ6fw/m8eZFHoQOy77sRqiRwtn89b3QQykR3z/daz53FyNon//ZLL2n7MxFoGO0N4y/Ub8NUnz+DMfHLtv2AhO2ZLxmG+9jefyOLnPvEocoUiPv9LN2Jzf32FQK1shRD4k1fvxC+8cBM++cAJfOqBkwa1ltqFfdedlC8IuamM2niAqtrslq+UEh+95xi2Dcbw8l3DVjenol+5dSuEAP7lvuNWN6Umu2VLxmK+9pYvFPGbX3oKE4tpfOJt12PbUEfdf3etbIUQeM+rd+HO3UP4wLeewz3PT7XaXGoj9l13Ur4gJCIyyn1HZnBoYhm/euvWhtfYtMu67jBes2cdvvLEGSymclY3h4hs6O++fxj3H5nB+1+/G9eM9Rj++B6PwN//9F7sGO7Eb37xKZxdSBn+HERkHOULQq4hVBvnuqvNbvl+6oETGOgI4jV71lndlJp+8UWbkcwW8KVHT1vdlKrsli0Zi/na18PHZ/Gxe4/hLTdswJuuH2v479ebbTTow0d/9hoUihK//eWnUShyPaETsO+6E6slcjROCVabnfI9Nh3HPc9P42dv3IiAz96Xzt3runDTll585sGTyBfs8zNcyU7ZkvGYrz0tp3N491f2Yaw3gvf8xK6mHqORbDf2RfF/XncFHj0xh4/da//Nroh9163s/a7GAPzFVlsqxWkoKrNTvp958CQCXg/eemPjd9St8Isv2oJzi2l898CE1U2pyE7ZkvGYrz391XcO4dxCCn//03sQCfiaeoxGs73rmlG8+soRfPgHR3B8Ot7Uc1L7sO+6k/IFIRFRqxKZPL76xBn8xJ4RDHQErW5OXW7fMYj1PWF84RH7ThslovbZN76ALzx6Gm97wea6jpcwihAC733tLgT9HvzJ1/bzKAoiG1K+IOQaQrVFIhGrm0Amsku+39h3DolsAT9z40arm1I3j0fgzddvwIPHZnFixn4H1dslWzIH87WXQlHiPV/fj/5YEL/9sm0tPVYz2Q52hPAHr9iBh47P4j+fPNvS85O52HfdidUSEdEavvjYOLYNxnDNWLfVTWnIT123AV6PwJce4yghkZv9++PjeObMIv701TvREfJb0oa33jCGPRu68dffPYRklmfdEdmJ8gUh1xCqLZm09+Hb1Bo75Hvw/BL2jS/gzTeM2e4g+rUMdYZw+45B/MfjZ5DN2+taaIdsyTzM1z5S2QI+9P3DuGasG681YIfkZrP1eATe8+qdmFrO4F/vP9FyO8gc7LvupHxBSETUii8/No6A14M3XD1qdVOa8pYbxzCbyOLug5NWN4WILPCpB09gajmDP3zlTstval23qRev2D2Mj997DNPLPACdyC6ULwi5hlBt4XDY6iaQiazON5sv4r+ePouX7x5CTzRgaVua9eLL+jHYEcR/PmWvdTtWZ0vmYr72sJjM4WP3HMNLdwzihs3GbCTTarZ/8ModyOSL+KcfHTWkPWQs9l13YrVEjsaCX21W53vv4WksJHN4wzXOHB0EAJ/Xg9ftXYd7np/CfCJrdXPKrM6WzMV87eETD5zAUjqP37vzcsMes9VsN/dHcdc16/GFR09jciltUKvIKOy77qR86lxDqLZEwn67J5JxrM73v54+i95oAC/eNmBpO1r1k1evR64g8c1nzlndlDKrsyVzMV/rxTN5fPqBE7hz9xB2jnQa9rhGZPvrL7kMhaLEx+89bkCLyEjsu+6kfEFIRNSMpXQOP3huEj9x1Qj8XmdfKnet68SO4Q7bTRslIvP828OnsJTO49duu8zqplxirC+CN1w9is8/cgpTyxwlJLKas9/l1IFD32oLBp1xSDg1x8p8v7t/Apl8Ea936GYyq73hmlE8dXoBJ21yJiH7rtqYr7XSuQL+9f4TePG2fuzZ0G3oYxuV7a+/5DLkCkV8+oGThjweGYN9151YLZGj+Xw+q5tAJrIy32/sO4ex3giuNvjNlFVefZW23fy395+3uCUa9l21MV9rff3ps5iJZ/DOW7ca/thGZbupP4o7dw/j84+c5rmENsK+607Kp67yGsLJpTTufX4aT43PY3Ipg3SugN5oAFv6o3jhZf24ZmOP46e6rSWRSHBHLIVZle98IosHj83iHbdssXybdqOMdodx9Vg3vvXMeVtMIWPfVRvztY6UEp964CR2DHfg5q19hj++kdn+0os34zv7J/DVJ87g527eZMhjUmvYd91J+YJQRU+dnsdH7jmG7z+nnSvWE/FjXXcYIb8XB84t4dvPnsc//vAoRrpCePsLN+OtN44hGmTURPX6/nOTKBQlXnXFiNVNMdSrrxzBB751EKdmE9jYF7W6OURkgkdOzOHQxDL++q4rbX9D65qxHuzd0I1P/PgEfubGjfB47N1eIlUpXyXY/WLYiMVUDh/81nP498fPoCvsx2+89DK86soR7BjuuOh1LqZyeODoDD770El88NsH8ekHT+Iv3nAlbt3u7J0SKwkEnHk2HNXHqny/s/881veEccWocTvz2cErSwXht561fpSQfVdtzNc6n37gJLojfrxurznrn43MVgiBX3zRZvzGF5/CPYen8NIdQ4Y9NjWHfded1J5PCHU2lXn2zCLu/NB9+OqTZ/HO27bigT98KX735Zdj50jnJUVvV9iPV105gi+942b8+6/cjJDfg//1yUfxgW8+h0JRWvQKzMELl9qsyHcxlcOPj87gVVeOKHVDCdCmje7d0I1vP2v9OkL2XbUxX2ucW0jhe89N4M3XjyHk95ryHEZn+4orhjHQEcQXHjlt6ONSc9h33UmNaqmGQqFgdRNa9j8HJvBTH38QXo/A137tBfiDV+xArM4poDds7sW3f+vFeNsLNuFff3wCv/iZx5DIqLN4Ox6PW90EMpEV+d59cBK5gsQrrxhu+3O3w6uuHMb+s0s4M5+0tB3su2pjvtb4jyfOoCiBt94wZtpzGJ2t3+vBm67bgB8emsK5hZShj02NY991J+ULQqf79rPn8c5/ewI7hjvxX7/+Qly1vrvhxwj6vHjfa3fjgz95Be47PI1f/MxjSGWdXygTmeF7ByYx3BnCnib6mhO8bJdW6N59cMrilhCRkYpFiS8/No4XXtaHsb6I1c1pyJtv2AAJ4EuPjVvdFCJXUr4gdPKUrx8emsRvfvEpXDPWg8//0o0Y6GjtbJifuXEjPvSmvXjkxBze8bnHkc07fwdWTm1QW7vzzeQLuP/INF66c1DZzQ0290exdSCKHxyctLQd7LtqY77t98CxGZxdSOFN15s3OgiYk+36nghu3T6ALz92GvmC89+bOBn7rjspXxA6dQ3hwfNL+PXPP4WdI5345C9cb9guoa/bO4q/vusq3H9kBu/97/2Q0tlrCnmAqtrane8jx+eQyBZwx87Btj5vu92xawgPH5/FUjpnWRvYd9XGfNvvy4+Nozvix8t3mbsxi1nZvuWGMUwuZXD/kRlTHp/qw77rTs6slhrgxDWEc4ksfvmzj6Mz7MMn/td16Az5DX38n75uA37ttq344qPj+NzDpwx97HbjXHe1tTvfuw9OIuT34AVb+9v6vO32sp1DyBUk7n1+2rI2sO+qjfm212Iyh+8dmMTr946atpmMzqxsX3L5IHoifnz1yTOmPD7Vh33XnZQvCJ1GSol3fflpTC1n8PGfuw6DnSFTnufdL78cd+wcxJ9/4zk8e2bRlOdoB6ePcFJt7cxXSokfHJzCiy4bMP0NldWuHutBbzRg6bRR9l21Md/2+s7+88gWinjDNeYcNbGSWdkGfB68bu8ovvfcJBZT1s1ecDv2XXdSviB02hrCzz18CvcdnsZ7Xr0Tezd0m/Y8Ho/A3/3UXgx0BPFbX37KsZvM+P3Gjp6SvbQz3+cnl3F2IaX8dFEA8HoEXnL5IO55ftqyo2jYd9XGfNvrv54+i839UVw52mX6c5mZ7RuuGUU2X7TF0Thuxb7rTsoXhE5aQ3hsOo6/+PZB3Lp9AD9700bTn68r4sff/dQeHJ9O4C++fdD05zMD57qrrZ35/vCQtuvmS3aoXxACwG2XD2AxlcO+MwuWPD/7rtqYb/ucX0zhkRNzeN3edW25CW5mtleOduGywRi++gSnjVqFfdednFMtNckpawillPijrz6LkN+L//vGq9o2svmCy/rx9hduxucePoUnTs215TmNlExae5Yamaud+d5/eAY7RzoxZNI0bbt50WX9EAKWrSNk31Ub822fb+w7BymB1+81f7ooYG62Qgj85NWjePzUvOVnpboV+647KV8QOsVXnzyLR0/O4Y9eucO0dYPV/O7Lt2OkK4Q/+dp+x233XCw6q73UmHblm8jk8fipOdyyTe3NZFbqiQawZ3037jtiTUHIvqs25ts+X3/6HPas78Km/mhbns/sbH/iqhEAwHeenTD1eagy9l13Ur4gdMIawoVkFn/57YO4ZqwbP3XthrY/fzTow3tfswuHJpbx6QdPtv35W+HzGXMcB9lTu/J95MQscgWJW7YPtOX57OLW7QPYN76AhWS27c/Nvqs25tsep2eTOHBuCT9x1bq2PafZ2W7s09ZCfpPrCC3BvutOyheETlhD+I93H8V8MosPvP5Kyw7DvnP3MG67fAAfvvsI5hPtf3PYrFDIHdP73Kpd+d53eAYhvwfXbuxpy/PZxS3bB1CUwI+Ptv/cL/ZdtTHf9vjOfq1oesUVw217znZk++qrRrBvfAHjc5y+2G7su+5k/2qpRXZfQzg+l8TnHj6Jn75uA3at67SsHUII/NErdyKRyeMj9xy1rB2N4lx3tbUr3/uOTOOmLX3KHzex2p71XegK+y1ZR8i+qzbm2x7f2T+BK0Y7saE30rbnbEe2r75Smzb6LY4Sth37rjspXxDa3d9+73l4PQLvumO71U3B5cMduOua9fjMg6ccs5ibc93V1o58z8wncXw6gRdvc9d0UQDweT144WV9eODoTNvPnmLfVRvzNd/5xRSeHl/AK68YaevztiPbDb0R7FnfhW89w4Kw3dh33YkFoYWeO7eErz99Dm9/4WYMd9ljiP53Xr4dQgAf/sERq5tSFydMCabmtSPfB4/OAgBe7KINZVa6eWs/zi2mcbrNU7PYd9XGfM333f3apivtnC4KtC/bO68YxrNnF3F+MdWW5yMN+647KZ+612vfKWD/70dH0BH04Vdu3Wp1U8pGusJ4641j+NpTZx0xdz8Sad80GWq/duT70PFZ9McC2DYYM/257OjmLX0AgAePzbb1edl31cZ8zfe9A5PYNhjD1oH2Xrvale3Ldw0BAH7w3GRbno807LvupHxBaNeh76NTy/jO/gn8rxdsQlfYb3VzLvKOW7bAIwQ+du8xq5uypnQ6bXUTyERm5yulxEPHZnHjlj5H7Ehshq0DUQx2BNteELLvqo35mmsxlcNjJ+fwslLR1E7tynbrQAyb+6P4HgvCtmLfdSflC8J2r4up10d+dAwhnxdvf9Fmq5tyiZGuMN543Xp85fEzmFi094Uhn89b3QQykdn5npxNYmIpXR4lcyMhBF6wtQ8PHZtt6/WSfVdtzNdc9x+ZRr4ocfvOwbY/d7uyFULgZbuG8PDxWSylc215TmLfdSvlC0I7Gp9L4uv7zuFnbhxDbzRgdXMqeuetW1GQEp984ITVTamJc93VZna+D5VGxW7e6t6CEABesLUfM/EMjk7F2/ac7LtqY77m+uHBKfRE/Ni7of1H5bQz25fvGkKuIC3ZCdmt2HfdSfnU7biG8DOlw99/8cX2Gx3UbeiN4BVXDOOLj55GImPfu0Wc6642s/N96PgsBjuC2NIfNfV57E4viNs5bZR9V23M1zyFosSPnp/CSy4fhNeCs4vbme3VYz3oiwbwfU4bbRv2XXdSviC02xrCeCaPLz8+jlddOYKRrrDVzanp7S/cjOV0Hv/55Bmrm1JVJpOxuglkIjPzlVLi4eOzuHmre9cP6jb0RjDaHS6PmLYD+67amK95nh6fx3wyh5daMF0UaG+2Xo/AbZcP4r4j0ygU7bkESDXsu+6kfEFotzWEX33iDJbTebz9hZusbsqarhnrxp4N3fjUAydRtOmFOJfjugKVmZnv8ZkEppczuMnF6wdXumFzLx4/Nde2ayb7rtqYr3nuPjgFr0dYdnZqu7O99fIBLCRz2Hdmoa3P61bsu+6kfEFoJ8WixKcfPImrx7px9Vj75/03SgiBt79wE47PJHDvEXvO33f7yI7qzMz38ZNzAIDrN/Wa9hxOcv2mXszEszg5257jZth31cZ8zXP/kRlcO9Zj2Q7l7c72lm398AjgHq4jbAv2XXdSviC00xrCB4/N4sRMAm97wSarm1K3V14xgr5oAF985LTVTakoFnPn2XFuYWa+j5+cR0/Ej60D7l4/qLths3aT6rETc215PvZdtTFfc8zGM9h/bhEv3tZvWRvanW13JIC9G7px7/NTbX1et2LfdSfbFIRCiP8thHhcCJERQny6wtdvF0IcEkIkhRA/EkJsrOdx7bSG8IuPnUZ3xI87dw9b3ZS6BXwevPHa9bj70BSmlux3BAXnuqvNzHwfPzWPazf28m5oydaBGHoifjx2sj0FIfuu2pivOR44NgspgRdvt2a6KGBNtrduH8QzZxcxG+fvldnYd93JNgUhgHMAPgDgk6u/IIToB/CfAN4DoBfA4wC+XM+D2mUN4Ww8g+8dmMAbrl6PkN8+o5b1eNP1G1AoSnzlCfttLpPNZq1uApnIrHynlzM4MZPA9ZvsP3W7XYQQuG5Tb9sKQvZdtTFfc9x/eBpdYT+uHO2yrA1WZHvb5QOQUpsuS+Zi33Un2xSEUsr/lFL+F4BK29y9AcABKeVXpJRpAO8DsEcIsaONTWzJV588g1xB4i03bLC6KQ3bMhDDTVt68aXHTtt2cxmiRjxxah4AcB0Lwotcv6kHJ2eTmFq232wAIreTUuL+IzN44WV9lhw3YaUrR7vQGw3gvsNcR0hkBtsUhGvYDWCf/oGUMgHgWOnzNdlhDaGUEl96bBzXbuzBtqEOq5vTlLfcMIbxuRQePtG+benrwbnuajMr38dPziHg8+AKC++y25G+wc7jJ+dNfy72XbUxX+MdnYpjYilt2e6iOiuy9XgEbt7ahweOzdhm5peq2HfdyWd1A+oUA7D6ttAigIrVlRDiHQDeAQCjo6NIp9PIZrPlYfBoNIp8Pl+eJx2NRlEsFpFKpQBcOJQzmdR22wuHw/B4PEgkEgCAYDAIn89X/jgQCCAQCCAej5c/DgaDiMfjkFLi+ek0jk8n8J47hzAzMwOfz4dQKIRkMolisQiPx4NIJIJ0Oo18Pl/+OJPJIJfLQQiBWCyGTCZTfg2xWKytr+mmDRFEg158+eHj2N4F+P1+BIPB8muw6jUtLy+X29hqTnZ5TUb+7jn9NSUSCfT09Bj+mh47OYvdwzEsL8xjmTmVX9OWHj+CPoEfHzqHW7d0mvqaUqkUBgYGbPu7Z+ecnPCa5ufn4ff7lXpNVuf0o4Pa4ey7+7xYWFiw7DVNT08jGo22Pae9w2F865kM9p2YwPpOv21zcvrvXjabRV9fn1KvScWcmnlNtYh23GkRQtwD4NYqX35ASvmiFd/7AQDrpZRvW/G5DwPwSyl/bcXnngXwPinlV2s99969e+XTTz/dfOMN8L7/PoAvPHoaj/3JHZZtE22Ed39lH/5n/wQe+9M7bLMOcmZmBv391u22RuYyI990roAr3vs/+KUXb8EfvtIxs87b5o0ffRASwFff+QJTn4d9V23M13jv+OzjODSxjPt+/yWWtsOqbE/OJHDb396DP3/dbvz8zZva/vxuwb6rLiHEE1LK6yp9rS1TRqWUt0kpRZU/L1r7EXAAwB79AyFEFMDW0udtLVco4hv7zuGOnYOOLgYB4CevHsVyJo8flO5SEjnRgXOLyBclrhnrtroptnT1WDeePbuIbN4+OzQTuV2xKPHIiTnctMW956Zu7ItgtDuMB4/aa+kKkQpss4ZQCOETQoQAeAF4hRAhIYQ+pfVrAK4QQtxV+p4/A/CMlPLQWo+71hCp2e4/Mo3ZRBY/efV6S9thhJu29GGoM4j/euqs1U0pi0Z5hpzKzMj3qdMLAIC9G7oNf2wV7N3Qg2y+iEMTS6Y+D/uu2pivsQ5NLGMxlcNNW/qsbopl2Qoh8IKtfXjo+CwK3ODONOy77mSbghDAnwJIAfhDAD9b+v8/BQAp5TSAuwB8EMA8gBsBvNmaZjbma0+dQ0/Ej1stPDPIKF6PwOv2juKe56cxn7DHtsT5fN7qJpCJzMj36fEFrOsKYbAzZPhjq+Dq0sipXjibhX1XbczXWA8f10bFbrRBQWhlti+8rB+LqRyeO2fuDSs3Y991J9sUhFLK91WYTvq+FV//gZRyh5QyXJqCerKex7XyYPp0roC7D07iFVeMIOCzzY+6Ja+5ah3yRYnvP2ePaaM8QFVtZuS778wC9nK6aFUjXSEMdgTx1Glzdxpl31Ub8zXWw8dnMdarTZm0mpXZvmCrVhA/eIznEZqFfded1KhSbOqe56eRzBbw6itHrG6KYa4Y7cT6njC+vf+81U0hathsPIPxuRSni9YghMDVY914enzB6qYQEbh+cKXBzhA290fx2Mk5q5tCpBTlC0Ir1xB+Z/959ET8Sl3EhRB41ZUjeODoDBaTOaubw7nuijM6X73I2bO+29DHVc3eDdoB9XMmTg1n31Ub8zWOndYPAtZne8OmXjx2ch5FriM0hdX5kjWULwitok0XncKdu4fh86r1Y37VlSPIFaQtdhu1ckowmc/ofJ8eX4DXI3Dleh5IX4u+jnCfiaOE7LtqY77G0UfDbthsj5vLVmd7w+ZeLKZyODy1bGk7VGV1vmQNtSqVCqz6xb7/yAzimTxeqdB0Ud2e9V1Y1xXCd2wwbVQ/4JPUZHS+T48vYPtQByIB39rf7GJXjnZBCOCZM4umPQf7rtqYr3EePzWP4c6QLdYPAtZnqxfGj57gtFEzWJ0vWUP5gtAq39l/Hl1hf3kBtEqEEHjFFSO47/AMEhnuRkXOIKXEM2cWsXcDRwfXEg36sKU/imfPmlcQElF9njg5h2s39UAIYXVTbGF9TxgjXSEWhEQGUr4gtGINYaEo8aNDU3jpjkH4FZsuqrtj1yCyhSLuP2LtTl+RSMTS5ydzGZnvmfkUFlM5XDHKgrAeV4x2Yb+JBSH7rtqYrzHOLaRwbjGN6zb2WN2UMquzFULg+k29ePTEHKTkOkKjWZ0vWUPNasViT56ex3wyhzt2DlndFNNcv6kXnSEf7rbBOkKiehw4pxU3V6xjQViPK0e7MLGUxvQytyAnssrjp7TjX661UUFoBzds7sXUcgan55JWN4VICcoXhFasIfzBc5PwewVu2d7f9uduF7/Xg9suH8QPD02hYOFOX8kk/zFQmZH5Pnt2EV6PwOXDHYY9psr0kVSzRgnZd9XGfI3x5Kl5hP1e7BzptLopZXbIVl9H+NhJc89LdSM75Evtp3xBaIUfHJzETVv60BHyW90UU92+cxCziSzPKyNH2H92CdsGYwj5vVY3xRF2r9PegHIdIZF1Hj81h70bupVdftKsywZi6Aj68NRpFoRERlD+CtPuNYQnZhI4Np3A7TsG2/q8Vrht+yC8HmHptNFw2B67rpE5jMpXSon9Zxe5frABHSG/qRvLsO+qjfm2LpHJ4+D5ZVy3yV7TRe2QrccjsHesG0+eXrC6KcqxQ77UfsoXhO2mF0e3K7x+UNcV8eP6TT344aEpy9pgxaZB1D5G5Tu5lMFsIosr1tln2pUTmLmxDPuu2phv6545s4hCUeIam60ftEu2V4/14PmJJe52bjC75EvtpXzq7V5DeO/haVw2GMOGXnfs0nTr9kEcmljG5FLakudPJBKWPC+1h1H56kUND6RvzJWjXTi/mMZM3PiNZdh31cZ8W7fvzAIAYM/6bkvbsZpdsr16rBtFeeHnRMawS77UXsoXhO2UyhbwyIk53LJtwOqmtI2+cY7Vx08Q1bL/3CKEgK02ZnCC3aPaz+vAuSWLW0LkPvvGFzDWG0FvNGB1U2zp6g3dAICnOG2UqGXKF4TtHPp+5MQssvkibr3cPQXhzuFO9MeCuO/wtCXPHwwGLXleag+j8t1/dglb+qOIBHyGPJ5b7BzWCsJD540vCNl31cZ8W7dvfAF7SkWPndgl2+5IAFsGotxYxmB2yZfaS/mCsJ3uOzyDoM+DG0vbIbuBxyNwy7Z+/PjoDIoWHD/h8/ENvsqMyvfg+SXs5vmDDeuJBjDcGcJBEwpC9l21Md/WTC2ncW4xjT02nOZup2yv3tCDJ08v8IB6A9kpX2of5QvCdq4hvO/ING7Y3Ou6be1v2T6AuUQW+8+1f3t6znVXmxH5LqVzOLuQ4vmDTdo50oFDE8uGPy77rtqYb2ueGdf+Pd1rwxFCO2V7zcZuzCWyPKDeQHbKl9pH+YKwXc4upHB0Ko5bt7tnuqjuRdu0dYRWTRslquX5UjGzc4QFYTN2jnTi6FQcmXzB6qYQuca+MwvwegRnNqxB33DnmTM8L5WoFcoXhEKItjzPj49oxdAtLiwI+2NB7BrpxI+Ptn9jmUCAi+1VZkS++vq3HcPcUKYZO0Y6kS9KHJsy9q4x+67amG9rnh5fwOVDHQgH7DfjyE7Zbh/qQMDnMe28VDeyU77UPsoXhO3aVObBY7PojwWxbTDWluezmxds7cOTpxeQzrV3FIEXLrUZke/BiWV0hnwY6QoZ0CL32VUaWTV6HSH7rtqYb/OklHjmzKItN5QB7JVtwOfBzpFOPMOjJwxjp3ypfZQvCAsF8wsUKSUeOjaLm7f2tW1E0m5u3tqHbL6IJ9u821c8Hm/r81F7GZHvofNL2DHS6dq+2apNfVEEfR4cmjC2IGTfVRvzbd74XAqLqRyusuGGMoD9sr1ytBP7zy5ZsrGdiuyWL7WH8gVhOxyfSWBqOYObt/RZ3RTLXL+5Fx4BPHxs1uqmEJUVixKHJ+PYyQ1lmubzerB9qAMHzxu/sQwRXUrfoO0Krh+sy1Wj3Yhn8jg5y81QiJqlfEHYjlGBB0tF0Au2urcg7Az5ceVoFx463t6CkFMb1NZqvmcXUohn8tjBA+lbou00yimjVD/m27wD5xbh8whsH7bnEhS7ZXtlaSSV6wiNYbd8qT2ULwjbsYbw4WOzGOkKYWNfxPTnsrObtvbh6fEFpLLtW0fIA1TV1mq+B8sbynCEsBU7hjsxE89iejlj2GOy76qN+TZv/9klbBvqQNBnvw1lAPtlu20whqDPw51GDWK3fKk9lC8IzV5DWCxKPHTc3esHdTdv6UOuIPH4qbm2PSfnuqut1Xz18/O2D7EgbIX+8zsyady0UfZdtTHf5kgpceDcInavs++sBrtl6/N6sHtdJ55lQWgIu+VL7aF8QWi2I1NxzCWyrl4/qLt+Uy98HoGH2zhtVEouIldZq/k+P7mMsd4IokGfQS1yp+1D2tS1I1PGvVFg31Ub823O1HIGM/EsrrBxQWjHbK9a34395xZR4MYyLbNjvmQ+5QtCs0ftHj2pjYbdxIIQ0aAPu0e78NjJ9u006vf72/Zc1H6t5nt0Ml4uZqh5Ax1BdIZ8OGzgCCH7rtqYb3MOlDaU2T1q3w1l7Jjt7nWdSGYL3FjGAHbMl8ynfEFo9hrCx0/OYagziPU9YVOfxymu29iDfeMLyOaLbXk+znVXWyv55gtFHJ+JY6tLzwY1khAC24c6DB0hZN9VG/Ntzv6zSxAC2GnjjbDsmK3+8zL6vFQ3smO+ZD7lC0Kz1xA+dmIO123qdf36Qd31m3qQyRfL22abLZlMtuV5yBqt5Ht6LolcQWLbINcPGmHbUAxHDSwI2XfVxnybc+DcIjb3RRGz8TR3O2a7bSgGn0fguXMsCFtlx3zJfMoXhGY6u5DCucU0rt/YY3VTbOPajb0AtJHTdigW2zMSSdZoJV99NGsbRwgNsW2wA3OJLGbixuw0yr6rNubbnAPnlrDLxusHAXtmG/R5cdlgjCOEBrBjvmQ+5QtCM0fu9KLn+s29pj2H0wx0BLGpL9K2dYQ+n33volLrWslXH83ilFFjbNM3lpk0ZpSQfVdtzLdxy+kczsynbD1dFLBvtrtGOvEcC8KW2TVfMpfyBaGZawgfOzmHWNCHHcP2vni323WbevHEqfm27FQVCoVMfw6yTiv5HplcxrqukK2nXjmJPvX2yJQxG8uw76qN+TZO37TJ7uem2jXbnSOdmFzKYNagWQxuZdd8yVzKF4RmriF8/OQ8rtnYA6+H6wdXum5jD+YSWRyfMX+3L851V1sr+R6djuMynj9omKHOIDpCPsNGCNl31cZ8G3fwvFYQXm7zgtCu2epTbfWfIzXHrvmSuZQvCM2ymMrh+cllrh+s4LpN7VtHyLnuams232JR4uhUnOsHDSSEwLbBmGFHT7Dvqo35Nu75iWV0BH0Y7bb3ruV2zVafavvceR5Q3wq75kvmYkHYpH3jC5ASuIYF4SW29EfRGfLh6fEF05/L7GNFyFrN5nt2IYV0rsiC0GBGHj3Bvqs25tu45yeWsX24w/a7lts1295oAMOdIY4Qtsiu+ZK5lE/d6/Wa8rhPjy9ACOCq9fY9PNYqHo/Ang3deOr0gunPFYlETH8Osk6z+eobylzGgtBQWwdimEtksZDMtvxY7LtqY76NkVLi0MSS7aeLAvbOdte6Th490SI750vmUb4gNGvo+6nT89g2GENHyG/K4zvd1Ru6cXhyGYlM3tTnSafTpj4+WavZfPWNT1gQGmtzfxQADFkfzL6rNubbmImlNJbSeex0QEFo52x3DHfg2HQc2TynPTbLzvmSeZQvCM3Y6VJKiafHF7B3Q7fhj62KvWPdKEpg/1lz5/Ln8+YWnGStZvM9MZNAXzSA7kjA4Ba52+YBrSA8Md16Qci+qzbm25hD5Q1l7L9ruZ2z3T7UgXxR4uSs+ZvaqcrO+ZJ5lC8IzXB6Lon5ZA57N3D9YDV71ncDgOnrCDnXXW3N5nt8OlEezSLjjPVG4PUInDBghJB9V23MtzGHJkoFoQN2RrZztttLP7/nJ7iOsFl2zpfMo3zqZqwh1IscjhBW1xcLYqw3YnpByLnuams23xMzCWxiQWg4v9eDsd4Ijs+0vrEM+67amG9jnp9YwkhXCF0R+y9DsXO2Wwai8AjtHFpqjp3zJfMoXxCasYbwqdMLiAS82D7E9Um17NnQbXpBmMnwAFqVNZNvIpPH1HKGI4Qm2dwfxXEDpoyy76qN+Tbm+cl4eXTL7uycbcjvxaa+KA4bdF6qG9k5XzKP8gWhGWsInxpfwJWjXfB5lf/xtWTvhm6cX0xjcsm8Bcq5XM60xybrNZOvPp1xCwtCU2zpj+LkbALFYmvXVvZdtTHf+hWKEsennXNuqt2z3T7UYdh5qW5k93zJHKxoGpTNF3Hw3BKni9ZB/xmZOUpo9/OaqDXN5KsXhJwyao7NA1Gkc0Wcb/FGD/uu2phv/c7Op5DJFx2zK7Lds90+FMPJ2QTSuYLVTXEku+dL5lC+IDR6DeHhyWVkC0VcyfMH17RrpBMeARww8UygWMwZ/4BSc5rJt1wQ9rEgNEP56Inp1qZkse+qjfnW7+i0s47JsXu224Y6UJQwZGq7G9k9XzKH8gWh0WsI9WMUrljHgnAt4YAXlw3GcMDEoyc4111tzeR7ciaBdV0hhAPGbyhF2uH0AFreaZR9V23Mt35Hp7SbK04pCO2e7eWlsxw5bbQ5ds+XzKF8QWj0GsJnzy6iI+TDxj7uwlSPK9Z14VkTC8JsNmvaY5P1msn3OHcYNdVgRxDRgLflu+/su2pjvvU7OhVHf8w556baPdtNfVH4PIIFYZPsni+ZQ/mC0Gj7zy7iinVdnGNdp92jXZhazmDKxI1liHRSapszcIdR8wghsHkgiuMGnEVIRFpBqI+8U+sCPg8290dZEBI1QPmC0Mg1hLlCEQcnlrl+sAFXjmo/K7PWEXKuu9oazXc+mcNSOs+C0GSb+qI42WJByL6rNuZbHykljk7FHTNdFHBGttuHOspTcakxTsiXjKd8QWjkGsIjk3Fk80XsXtdp2GOqblfpZ7XfpGmjnNqgtkbzPVE6MJ0FobnGeiM4u5BCvtD89ZV9V23Mtz7T8QyW0nlHFYROyHbLQBTj8ylk88afRa06J+RLxlO+IDRyDaFe1OijXrS2WNCHLf1R09YR8sKltkbzPTmTBMAjJ8y2sS+CQlHi3ELzU8HZd9XGfOvjtA1lAGdku2UgikJR4vQcp7Y3ygn5kvGULwiN9OzZRcSCPm5n36Ddo12mHj1BpDs9l4QQwPqesNVNUdqGXm1TrdNzSYtbQuRsxxxYEDrBln7t53mMR08Q1UX5gtDjMe4l7j+3iF3rOuHxcEOZRlyxrhNnF1KYSxh/1ykaZXGuskbzHZ9LYqQzhKCPR06YaWPpptipFu6+s++qjfnW59h0ArGgD8OdIaubUjcnZLtlQGvjsRbPS3UjJ+RLxlO+IDRKsShx6Pwy1w82QV9HeOi88aOE+Xze8Mck+2g039NzyfLoFZlnuDMEv1e0NELIvqs25lufY6VdkZ20c7kTsu0I+THYEeTh9E1wQr5kPOULQqM2lTk1l0QqV8DOYRaEjdpR+pkdnDB+C2geoKq2RvM9PZfEGAtC03k9Aht6IhhvoSBk31Ub863PydmE4zbBckq2WwaiOM4RwoY5JV8ylvIFoVH00a0dIx0Wt8R5BjqC6I8FTBkhJNKlcwVMLWc4QtgmG3ojODXLNYREzcrmizg7n+ImWCbZMhDjealEdVK+IDRqDeHBiWV4hHa2DTVux3AnDpkwQsi57mprJN8z81pxwhHC9tjYF8Hp2WTTOzmz76qN+a7t9FwSRQls7nfWNcsp2W7pj2IhmTNl/wKVOSVfMpbyBaFRDp5fwub+KEJ+blbRjB3DHTg8uYxC0bhjQABjz5kk+2kkX309G0cI22OsN4LlTB4LyVxTf599V23Md20nS6NXTtu53CnZbh3QdxrltNFGOCVfMpbyBaFRv9iHJpawY4TrB5u1Y6QTmXwRJ2eNnb6RSqUMfTyyl0byPT3LEcJ2Gmvx6An2XbUx37Xp/x46bQ2hU7LVC0KuI2yMU/IlYylfEBphOZ3D+FwKu1gQNm3HsDbV9tB546eNEgHA6bkUwn4v+mMBq5viCheOnuA6QqJmnJhJoDviR3eE1ywzjPaEEfB5uNMoUR2ULwiNWEP4fGntm17UUOMuG4zB6xE4NGHsxjKRCEeDVNZIvuPz2g6jTtq+3ck29IYBoOmdRtl31cZ813ZiJuG46aKAc7L1egQ29UW4sUyDnJIvGUv5gtAI+nEJnDLavJDfiy39URzkCCGZZJxnELZVJODDQEcQpwyeBk7kFidnnHfkhNOM9UbLywmIqDrlC0Ij1hAePL+EzpAP67pCBrTIvXaMdBo+QphM8kKvsnrzlVLyDEILbOgJ48x8c+tN2HfVxnxrS+cKOLeYduQIoZOy3dgXwam5RNO7IbuRk/Il4yhfEBrh8MQyLh/u4FS0Fu0Y7sCZ+RTimbzVTSHFzCaySGYL5WmM1B7rusM4u8ANCIgapZ/huclhR044zaa+CNK5IqaWedg6US3KF4StriGUUuLIVBzbeP5gyy4bLG0BPWXcjl/hMAsAldWbr76ObUMP31y102hPGOcX0ig2cZwM+67amG9tJ0rr2rb0xyxuSeOclO2YvvkVp43WzUn5knGULwhbNR3PYDGVw7ZB51207Ub/GR4xsCA0YtMgsq968z23kAYArOcIYVuNdoeRLRQxE2/87jv7rtqYb236kRMbHThC6KRsN5aWERh95JXKnJQvGUf51FtdQ3h0UitetnOEsGVjvREEvB4cmTJuY5lEghd5ldWb77nStMV13SwI22m09PM+08S0UfZdtTHf2k7PJdEbDaAz5Le6KQ1zUrajPWF4PYIbyzTASfmScWoWhEIInxDiDUKITwghHhdCHC399xNCiDcKIXztaqhV9NEsjhC2zuf1YMtA1NApo0QAcHYhhY6gz5FvrpxstEcrCM9xHSFRQ8bnktjQwxtYZvN7PRjtDnOEkGgNVQtCIcSvAjgO4FcAHAPwQQC/WvrvMQC/DOB46ftsq9Wh78OTy+gMadurU+u2DsYMnTIaDDIXldWb77mFFEcHLaD/zM82sdMo+67amG9t43NJrHforshOy3ZjXwSnmzwv1Y2cli8Zo9YI32UAbpBSTlT42tcA/IUQYgTA75rSMpvQN5ThDqPG2DYYw7efPY90roCQ39vy4/l8yg9Su1q9+Z5bTGFdN4+FabfOkB8dIV9TI4Tsu2pjvtUVihJnF1J4xRUjVjelKU7LdmNfBN/Yd97qZjiG0/IlY1QdPpNSvrtKMbjye85LKd9tfLOM0/Iawqk4tg9xuqhRtg12QErg2LQxo4Sc6662+tcQpjlCaJHRJo+eYN9VG/OtbnIpjVxBOvaYHKdlu7E3isVUDgvJrNVNcQSn5UvGqPs2gBAiAm3U8KLqSEr5oNGNsovZeAZziSwuG+SGMkbZViquj07FsXtdl8WtIRWksgXMJbIsCC0y2t384fREbsRjctprY5/2cz41m0R3JGBxa4jsqa4FdkKInwcwAeCHAL684s+XjGiEECJY2qjmlBBiWQjxtBDilau+53YhxCEhRFII8SMhxMY6H7vpdnFDGeNt6ovC6xE4MmnMCGEgwIu7yurJ99yiVoyMsiC0xGhPuKkpo+y7amO+1enr2TY4dA2h07LdqJ9FyHWEdXFavmSMendc+RsAd0kp+6WUG1b8GTOoHT4A4wBuBdAF4E8B/LsQYhMACCH6AfwngPcA6AXwOLSCdE2tbCpTLgg5ZdQwAZ8Hm/oiOGrQxjK8cKmtroKQR05Yal13GEvpPJbTuYb+Hvuu2phvdePzKQgBx657dlq2Y6XC+9QMp0LWw2n5kjHqrZayAO4xqxFSyoSU8n1SypNSyqKU8psATgC4tvQtbwBwQEr5FSllGsD7AOwRQuxY67ELhULT7To6uYxY0IfhTmdetO3qssGYYWcRxuM8wkJl9eR7oSBkP7WCPjLb6DpC9l21Md/qzswlMdIZQtDX+sZqVnBatuGAF/2xIKe218lp+ZIx6i0I3wPg70sjdaYTQgwB2A7gQOlTuwHs078upUxAO/pit5ntOD6TwJaBKHcYNdiWgRhOzyWRL7S24Q8RAJxdSMMjgCHeuLEEzyIkasz4vHOPnHCq9T3NbX5F5Bb1bipzGMCfA/i1FcWRACCllIbe4hJC+AF8HsBnpJSHSp+OAZhe9a2LACru9iKEeAeAdwDA6Ogo0uk0stkssllth6loNIp8Po9MJlP+uFgsIpXSLhaRiHahPja5jKtGY0gkEvB4POWdl4LBIHw+X/njQCCAQCBQvqsSCAQQDAYRj8chpYTf70cwGEQymUSxWITP50MoFCp/7PF4EIlEkE6nkc/nyx9nMhnkcjkIIRCLxZDJZMqvIRaLNfWakkltDn04HLbsNQ0EJXIFiRNTixiKelt6TYVCATMzM5a/JhVzssNrSiQSa76mk1OLGOwIYnlxwRGvSbWcwkXt7x89P48Xbu6u+zWlUimk02lbviYVc2r3a8rlcuVrsyqvyaicTs3EcdOWXqRSKUe+Jr3NTsppIOLBocllpFIpV//u1fOastksMpmMUq9JxZyaeU21CCllzW8AACHEUQBfhLZu76JbLFLKY3X8/XugrQ+s5AEp5YtK3+cB8AUAnQBeJ6XMlT7/YQB+KeWvrXjMZwG8T0r51VrPfe2118onnnhirSZeIp0rYOeffRfvun07fuuObQ3/faru8ZNzeOPHHsKnfuF6vOTywZYeK5PJ8BBVhdWT71v/5WFk8kV89Z0vaFOraKViUeLy93wHb3/RZvzRK3fW/ffYd9XGfCtL5wrY8Z7v4l13bMO77thudXOa4sRs//I7B/GpH5/Eofe/Ah4PZ33V4sR8qT5CiCeklNdV+lq9U0b7APyZlHK/lPLYyj/1/GUp5W1SSlHlj14MCgCfADAEbQOblTsUHACwZ8ULigLYigtTSqtqdg3hqdkkpAQ2D0Sb+vtU3eZ+7Wd6Yrr1Bd6c6662etcQckMZ63g8AoMdIUwuphv6e+y7amO+lenTFp185IQTs13fHUa2UMR0PGN1U2zPiflS6+otCD8F4OfMbAiAjwLYCeA1UsrVE72/BuAKIcRdQogQgD8D8MyKKaWGOzGjdYgt/SwIjdYbDaAj5MMJA3b8qmeEm5xrrXyLRYlzi2luKGOx4a4QJpcae6PFvqs25lvZuMOPnACcme36UgHOjWXW5sR8qXX1FoQ3APhXIcTzQoj7Vv4xohGlMwV/BcBeABNCiHjpz88AgJRyGsBdAD4IYB7AjQDeXOdjN9Wm46ViZRMLQsMJIbClP2pIQej3+w1oEdnVWvnOJrLI5otY18URQisNd4YwudTYCCH7rtqYb2V6QbK+x7nXLCdmq29+xY1l1ubEfKl19W4q8y+lP6aQUp6CtklNre/5AYA1j5lYrdlzCI9PJzDUGUQsWO+PiBqxuT+Kx07Ot/w4nOeutrXy1YsQ7jBqraHOEH70/BSklHXfhGPfVRvzrez8Ygpej3D0NcuJ2erH45yZ5+H0a3FivtS6uqodKeVnzG6IWZpdQ3hiJlFe60bG29wfw9f3nUM6V0DI3/xGtclkEqGQc/9hpdrWyndqWS8I+Q+YlYY6g0hmC4hn8ugI1Xd3mX1Xbcy3snMLaQx3huB18MYmTsw2GvShJ+LHWU4ZXZMT86XW1TV8JoR4ixBiZ+n/LxdC3CuE+FE9B8M7lVYQxqxuhrI2D0QhpbZ5TyuKRZ5lqLK18tXXrTn5brsKhru0n38j00bZd9XGfCs7t5DCSJezr1dOzXa0J8w1hHVwar7UmnrnU34AwFzp//8WwGMA7gXwETMaZaRm1hAuJLOYS2S5oYyJNveVdhqdaW03K5+PU3pVtla+egEy0MERQivpBfnEYv0by7Dvqo35VnZ+MY0Rh++K7NRs13dHuIawDk7Nl1pTb+oDUsrJ0g6fLwLwRgA5ADOmtcwgzawh1DeU2cIjJ0yzqV/b8et4ixvLcFqD2tbKd3Ipg/5YAH5vc2uFyRh6QdjICCH7rtqY76WKRYmJxTReeaWzfzZOzXa0J4x7D083tNbZjZyaL7Wm3ndR00KIywC8EsBjUsoMgBDW2AjGDppZQ6ifj8c1hObpCPkx0BFs+SzCZJILxFW2Vr5TS2kMdvAfL6sN6yOEDRSE7LtqY76XmklkkC04f1dkp2a7vieMVK6AuUTW6qbYmlPzpdbUO0L4fgBPACgAeFPpc3cA2GdGo6x2ai4Jj7hwbg2ZY3NfFCdnWysIOdddbWuuIVxOc0MZGwgHvOgM+biGkMqY76XOL2j9g2sIraHvNHp2IYW+GP/dqMap+VJr6hohlFJ+GsAIgPVSyu+XPv0w6jwL0GlOzyYw0hVGwMdpaGba0BvB6bnW7kQ1e6wIOcNa+U4sZrihjE1oh9PXXxCy76qN+V7q/KK2fm2dw9cQOjVbHk5fH6fmS62pO3UpZVJKmRRCBIQQ1wDISiknTGybIbzexo80OD2XxMY+jg6abaw3gsmlDNK55o4GAYBIhDmprFa+uUIRswkWhHYx1BnCxFL9m8qw76qN+V7qbGmE0OkFoVOz1UcIz3FjmZqcmi+1pmZBKIToFEL8vRDiu0KI9wohRgAcBPA4gDNCiDva0soWNDP0fXouhbFedgizjfXpB8U2f3FOp+sfkSDnqZXvTDwDKXnkhF0MdYYwuVh/f2TfVRvzvdT5hRSCPg96IvWd1WlXTs22M+xDyO9paCaDGzk1X2rNWiOEHwWwE8DXAbwAwN0APgwgBuAPAXzQ1NYZQErZ0PcnMnnMxDPYwILQdHrRPd7CtNF8Pm9Uc8iGauV74QxCrgWxg+HOEKbjGRSK9V1z2XfVxnwvdX4xjdHusON3uHRqtkIIjHSFcb6BG1du5NR8qTVrbSrzMgBbpJRxIcSXAEwB+CcpZUEI8RFo5xMqZXxeK044Qmg+vehuZR0h57qrrVa++l1ejhDaw1BnEIWixGw8g8E6MmHfVRvzvdS5xRRGup1/vXJytkOdQY4QrsHJ+VLz1ko9JKWMA4CUch5AXEpZKH1crOPvW67RNYSnZ7XihGsIzTcQCyLk97RUEHKuu9pq5TtV+kd9kCOEtjDU4NET7LtqY76XOreQwojDj5wAnJ0tRwjX5uR8qXlrFXRCCLFZCLFFCLGl0sdtaGNLGl1DqBcnHCE0nxACYy3uNJrJ1L+JBTlPrXwnlzLwegT6oiwI7WC4Sz+cvr4+yb6rNuZ7sVyhiKnljOM3lAGcne1QZwhTSxkU65za7kZOzpeat9aU0SiAo7i48Du24v9t36MaXUN4ei6JjpAPXWFnL/p2irHeSEtrCHO5nIGtIbuple/kUhoDsSC8Htvfl3KFRkcI2XfVxnwvNrmUhpTAOoefQQg4O9uRrhCyhSLmkln08yzCipycLzWv5gihlNIjpfSW/lvpT+NnOtjc6bkkxnojjl/07RT6WYSNFu465qS2WvlOLme4oYyN9EUDAICZ5fruLrPvqo35XkyfpjiiwAihk7Mt37jitNGqnJwvNc/2awBb1fAaQp5B2FZjvREkswXMJrJN/f1YLGZwi8hOauU7tZSua/MSag+fV9tOfyZeX0HIvqs25nuxC5tgOf8mlpOzHeliQbgWJ+dLzas6ZVQIcT/qmBIqpbzF0BYZrJE1hIWixJm5FF62a8jEFtFKK4+eaGb6RiaTQTDo/H9gqbJa+U4upXHdpp42t4hq6Y8FMRuv7+YO+67amO/FpvRjcjqcfxPLydnqa53Pc6fRqpycLzWv1hrCf13x/1sBvB3AZwCcAjAG4H8B+KR5TTNGI1MRJ5fSyBaK3FCmjcZWHD1x9Vjjb+6z2eZGFskZquWbKxQxn8xhIOb8N1cq6Y8F6x4hZN9VG/O92ORyGgGvB90OP5QecHa2/aV155McIazKyflS86oWhFLKz+j/L4R4GMCdUsoDKz73BWgF4XtNbWEbcYfR9lvf0/rh9OQ+86Upxn2xgMUtoZX6O4J49syC1c0gsp3ppQwGOoJcn2Uxr0dgsCPIoyeIVql3DeFOXLy7KACcALDD2OYYr5E1hGfmUwAuFClkvnDAi4GOYNNHT3Cuu9qq5TtTmpbYz4LQVvqigbqnjLLvqo35XmxyOa3MmalOz3a4K8TD6Wtwer7UnHoLwnsBfFoIsU0IERZCbAfwCQD3m9c0YzSyhvDcglYQjiiwLbSTjHaHcW6huYszpzaorVq++rTEPm4bbisDHUEsZ/JI5wprfi/7rtqY78WmljJKrB8EnJ/tcGcI5xdTVjfDtpyeLzWn3oLwbaX/HgAQB/AstLMJf8GENhmqkTWEZ+dT6I8FEfIrd5qGrWkFYXMXZ1641FYt39lEqSCMcoTQTvQR23rWEbLvqo35XmxqOaPMCKHTs9VGCHn4ejVOz5eaU1dBKKWck1K+GUAIwDoAYSnlW6SUM6a2rs3OLaYw2uP8M4KcZl13CGcXUk2fRUjuo09L5AihvfRFtTxm6pw2SuQG6VwBi6kcBjt4vbKD4c4Q4pk8ltM8gJ1IV7UgFEJccvaClLIopZyUUhZrfZ+deDz1H7V4diGF0W41pnQ4ybruMDL5IuaaOIswGo2a0CKyi2r5zsSzCHg96AzV2iiZ2q2/9IZ3to4RQvZdtTHfC6aXtf6gyrmpTs9WP3qC6wgrc3q+1Jxa1dIPhRAfEULcLIS46PuEEB4hxE1CiI8AuNvcJraHlBLnFlIY7eYIYbvpP/Nm1hHm83mjm0M2Ui3f2XgGfbEAd+yzmUamjLLvqo35XqAXHqqMEDo92+FSYc6dRitzer7UnFoF4dUAngPwLwCWhRDPCiEeFEI8C2AJwMegrSW8xvxmNq/eTWXmElmkc0WsY0HYdvrP/OxC4zuNZjJcB6CyavnOJrI8csKG+mP1Txll31Ub871gqjRCOKTICKHTsx3o0K9Tzn4dZnF6vtScWucQZgH8PwD/TwixAcCVALoBzAN4Rkp5ti0tbJOzpU1NOELYfqPlgpB366g+s/FMeb0a2UfI70Us6CtPkSMiYEqxEUKn06e2zyxzrTORrq4FOFLKcQDjJrfFFPWuIdR3ueQIYft1R/wI+71N7TTKue5qq7WGcOsgz0qyo/5YALN1rAdm31Ub871gcjkDv1egJ6LGrAanZ9sR9CHo82CaI4QVOT1fak79O64oTj+UniOE7SeEwLruUFMFYSPnTJLzVMpXSomZeKY8PZHspT8WxEwdI4Tsu2pjvhdMLWUwEAvC41FjzbPTsxVC1H2dciOn50vNUb4grPcX+9xCGpGAF90Rv8ktokrWNXkWYSrFw2VVVinfRLaATL7IMwhtqi8WqGttDvuu2pjvBVPLaWV2GAXUyHagI8gRwipUyJcap3xBWK+zC0ms6w5z10KLjHaHuYaQ6qIfacAzCO2pPxasa8ookVtMLWW4ftBm+mNBrnUmWqGhgrB03MSIWY0xQ/1rCNOcLmqhdd1hzMQzSOcKDf29SCRiUovIDirlO1M+lJ4jhHbUHwtiPplFvlB7dgb7rtqY7wWTy2kMdqpTEKqQ7UBHsK7dkN1IhXypcXVVS0KIbiHEFwCkARwtfe61QogPmNm4djq7kOKGMhbSf/YTPBeI1qCPEA5whNCW+mMBSKkd5UPkdpl8AQvJHIY61JkyqoKBWABziQwKRWl1U4hsod4Rwo8BWASwEYD+r/xDAN5kRqOMVM8awlS2gLlEFut7WBBa5cLRE43NXU8mGz+7kJyjUr76dESOENqTvtnPWutz2HfVxnw1+ijUgEJTRlXIdqAjiCJvXFWkQr7UuLqOnQBwO4B1UsqcEEICgJRyWggxaF7T2ufcolaEjHTxDp5Vmi0IyX30EcJebipjS+Uzvjgdi4hrnm2qfONqOaNUsU7UrHpHCBcB9K/8hBBiDMB5w1tksHrWEE6WpikOsyC0jP6zb3Sn0XCYo7oqq5TvTDyLjpAPQZ/XghbRWnpKOzUvJGsXhOy7amO+GhVnNKiQ7UD5xhU3lllNhXypcfUWhP8K4KtCiJcA8AghbgbwGWhTSR1vcrlUECq0LbTTBHwe9EUDmGpw1696Nw0iZ6qUL88gtLfu0uHbC8lcze9j31Ub89XM6ptgKTSjQYVsV44Q0sVUyJcaV2/qfw3gywD+CYAfwCcBfB3Ah01ql2HqWUM4sahdEIZYEFpqsDOEqaXGNpVJJBImtYbsoFK+s/GsUm+uVNMV1kcIaxeE7LtqY76auYR6U0ZVyJYjhNWpkC81rq41hFJKCa34s30B2IzJpTQ6gj5Eg/UuqSQzDHUGMdFgQUjuM5fIYmMft8W2K7/Xg46gD/NrTBklcoPZeBYBnwfRAKe420k06EPY7+UIIVFJ1QpICPHSeh5ASvlD45pjvLrWEC6pdUaQUw11hHDg3FJDfycYZG4qq5TvQiqLvZHu9jeG6tYV8WMxVXuEkH1XbcxXM5vIoj8agBDC6qYYRpVstbMIWRCupkq+1JhaQ2KfWPXxKAAJYBZAHwAB4AyALeY0rX0ml9LcUMYGhrpCmIlnkC8U4fPWN5vZ5+Oorsoq5buQzKG7tHEJ2VNPJLDmCCH7rtqYr2Y2nkGvQhvKAOpk2x8LrHk8jhupki81puq7binlZv0PgH8B8P8B6JFSrgPQA+AfS5+3tXrWEE4uZXhorA0MdQYhZWPb1XOuu9pW55vOFZDJF9HFgtDWuiN+riF0OearmUtk0RtVa8RFlWwHOoKYWebU9tVUyZcaU++mMr8N4A+llEkAKP33jwD8jlkNa5diUWJqOY0hjhBaTi/KJ7mOkKrQi4zusFp33FXTHQmseewEkRvMxLUpo2Q//bEgRwiJSuotCBMAblj1uesBJI1tjvHWmrc/l8wiV5AY4sGkltN3eW1kY5lAgP/Qqmx1vgsprcjglFF76w77sbDGGkL2XbUxX402QqjWz0KVbAc6gphPZpErrD2TzE1UyZcaU+9E4fcA+K4Q4hsAxgFsAPATAH7drIYZZa1NZfTRKK4htN5Ql1aUN3L0BC9carukICyNEOpHG5A99ZQ2lSkUJbyeyjfl2HfVxnyBZDaPVK6g1JETgDrZ9se0ZSpziSyPHVtBlXypMXWNEEopPwfgRgAHAXQCOATgptLnba1QKNT8ul4QDvJiYLm+aBBej8DkUv1TOOLxuIktIqutzlffuZIFob11RQKQElhOVx8lZN9VG/NV81B6QJ1s9VzmEpzevpIq+VJj6t5KSEr5HIDnTGyLJfTiY5gFoeW8HoGBWJBrCKmqRX0NIaeM2lpPKZ/5ZA7dEbXeDBPVSy80+hTbZVQV+rWJZ6YS1VkQCiE+B+3IiUtIKX/e0BYZbK01hBOLaQihzSUn6zV6OD2nNqit+hpC5m5nPaV8tI1lohW/h31XbcwXmE1oN5y5htCeeqLajau1dkR2G1XypcbUu6nMUQDHVvxJAHglgDmT2mWYtdYQTi2n0RcNwl/nuXdkrqHOEKYamDLKA1TVtjrfhWQOPo9ANOC1qEVUD/1YkFpvtNh31cZ8V04ZVetnoUq2vRFOGa1ElXypMXWNEEop/8/qzwkhPgHgvYa3yGBrrSGcWExjuIu//HYx1BnCoyfrv88Qj8d58VLY6nwXUtqh9GuN/JO1yiOEqepvtNh31cZ8gVlFp4yqkm33RTMZSKdKvtSYVobFngZwq0HtsAwPpbeXoc4gFpI5pHO1C3mdlBVnMpMiVue7mMxxQxkH6A6vPULIvqs25quNPAV9HkQUm9GgSrYBnwfRgBfznDJ6EVXypcbUu4bwpas+FQHwZjhgk5m1RhIml9LYO9bdnsbQmvTdXqeXM9jQG1nz+/1+FgcqW53vQirL9YMO0Bn2QwjUfKPFvqs25gvMxDPojwWVm9GgUrY90QDmOWX0IirlS/Wrd5fRT6z6OAFthPAthrbGBLXWEGbzRcwmshjkhjK2MbzicPp6CkJOa1BbpTWE3BHY/rwegc6QH4s1pmKx76qN+ap5KD2gVrY9kQB3GV1FpXypfvWuIdxsdkPMUmsNob6QmDuM2od+OGy9R08kk0mEQiwQVLU638VUDpcPd1jYIqpXT8Rfc4SQfVdtzFfbVEa19YOAWtl2r3GdciOV8qX61bWGUAjxVJXPP25sc9prJq7tZtkfY0FoF/2lfzz13dnWUiwWzWwOWWx1vlxD6BxdkQAWUtXfaLHvqo35qjtCqFK2HCG8lEr5Uv3q3VTmstWfENqk+C3GNsd4tebuXygI1btgO1V3JACPAGbj9R094fPVO+uZnGhlvrlCEcuZPLrD7K9O0BPx19y9j31XbcxXO4ewT8GCUKVse7mG8BIq5Uv1q5m6EOKzpf8NrPh/3SYAB8xolJFqrSGcKY1CcYTQPrwegd5oANN1jhByWoPaVua7VBpt6o5whNAJusN+HJ9OVP06+67a3J5vOldAOldUchMslbLtjvixlM4jXyjCx/OoAaiVL9Vvrd9+/SD6lf9/DNpB9Z8H8DrzmmaMWmsI9VGoPhaEttIfC9Y9QphMJk1uDVlpZb4LLAgdpXuNqVjsu2pze776DSwVp7irlO2FM1O5jlCnUr5Uv5ojhPqB9EKIh6WU/9OeJrXPTDyDkF87h4bsoy8WKB/ouxbOdVfbynz1M+1UfIOlou6IH8s17ryz76rN7fkuKFwQqpRtT/TC4fScLaZRKV+qX9WCUAhxi5TyvtKHuQpnEQIApJQ/NKVlbTAbz6Ivqt4ZQU7XFw1i35mFur631pRgcr6V+S6mtJsEKk7BUpF+530xlas4C4N9V21uz3dR4YJQpWx7SjNOuNPoBSrlS/WrNUL4EQBXlP5/9TmEOgmbbyzj9VYf/ZuOZ9DPIydsR5syWt8IYSSy9lmF5Fwr89VHCLsVfIOlIn1q70KVgpB9V21uz3dR4RkNKmWr37ia48YyZSrlS/WrWhBKKa9Y8f+OPYew1tD3bDyLkS4unrWbvlgA8Uwe6VwBIX/t6bzpdJoLoBW2Mt9yQcg1hI4QC2r/vMTT+YpfZ99Vm9vzXVR4zbNK2a6cMkoalfKl+ik/LiylrPq1mXiGc8ZtSD8GZKaOjWXy+cpvNkkNK/NdTOUgBNARUu8NlorKBWGmch9l31Wb2/NVecqoStlyyuilVMqX6ldrDeE4tCmhNUkpxwxtUZsUixJziSz6eAah7ehF+mw8i/U9tacucK672i5eQ5hDZ8gPr4drfp0gFtL+eVmuMkLIvqs2t+erbyqj4g0slbIN+70I+Dw8i3AFlfKl+tVaQ/izbWuFiaqtIVxM5ZAvSo4Q2pC+3mg2sfYIIee6q+3iNYRZJe+2q6ojqGVVbYSQfVdtbs93KZVDR8in5A0slbIVQqAn4q95RI7bqJQv1a/WGsJ729kQs1RbQ6gXGxwhtJ++qD5ldO0LdCaT4Vx3ha3MdymdR2e45kk5ZCP6CGE8XXkqFvuu2tye72Iqp+wNLNWy7YkEOGV0BdXypfrUNS4shAgIIf5cCHFECJEo/ff9Qgjb/8ZUW0M4vawVGwMcIbQdfdS2njWEuRwv4ipbmW88nS+vSyP7iwa12RnVRgjZd9Xm9nwXUzklN5QB1Mu2JxLglNEVVMuX6lPvROGPAngpgN8EcH3pv7dBO5rCkfRio9J26GStcMCLaMBb19ETPENSbSvzjWdYEDpJ0KetzVmuUhCy76rN7fmqPEKoWrY9UU4ZXUm1fKk+9b67ej2ArVLKhdLHzwkhHgFwFMDbTWiXYaqtIZwtFYT9nDJqS32xYDmjWmKxWBtaQ1ZZmW8iy4LQaTqCvqrHTrDvqs3t+S4ks7h8uMPqZphCtWx7IoHysUakXr5Un3pHCCcArF5lGgZw3qiGCCH+TQhxXgixJIQ4LIT4pVVfv10IcUgIkRRC/EgIsbGex622hnAmnoVHAN0RFoR21BcL1L2GkNS1Mt94Oo8oC0JHiYV8VaeMsu+qze35Lqbyyo4QqpattoYwW/OYMjdRLV+qT70F4ecAfFcI8ctCiFcKId4B4NsAPiuEeKn+p8W2/CWATVLKTgCvBfABIcS1ACCE6AfwnwDeA6AXwOMAvlzPg1br4LOJDHqjQSV3AFNBfyxY1xrCbJbTPFS2Ml9OGXWeWI0RQvZdtbk5XyklllI5dIXVvOGsWrYdIR+KEkhmC1Y3xRZUy5fqU++7q18p/fePV33+V0t/AO3Mwi3NNkRKeWDlh6U/WwE8AeANAA5IKb8CAEKI9wGYEULskFIeaub5ppeznC5qY/2xAJ4eX7C6GWQTuUIRmXyRBaHDxIK+qmsIiVSVzhWRLRSVHSFUjX5W5DJnoZCL1fWbL6XcbHZDAEAI8REAb4M2HfUpaKOQALAbwL4V7UkIIY6VPl+zIKy6hjCR4RmENtYXDWIukUWxKOGpMYrLue5q0/NNlIoK/mPtLB0hH84tpCt+jX1XbW7Od7F0KL2qBaFq2XaUjshZTucw3GX7zfNNp1q+VB9bvbuSUv6aEOI3ANwMbRdTfc5gDMD0qm9fBFBxxXZpSus7AGB0dBTpdBrZbLY8DB6NRjG1lMaVI1HMzMwgGo2iWCwilUoBuHAoZzKZBACEw2F4PB4kEgkAQDAYhM/nK38cCAQQCAQQj8fLHweDQcTjcUgp4ff7EQwGkUwmUSwW4fP5EAqFyh97PB5EIhGk02nk8/nyx5lMBrlcDkIIxGIxZDKZ8muIxWKXvKZ8Pl+e++301xQSORSKEmem5xHxFqu+puXl5XIb7f6aVMzJ7NeUSCTQ09ODuZT2OyBzKSwuLjr6NamYU7XXFPZ5sJTKYGZm5pLXlEqlMDAw4LjXpGJOZrym+fl5+P1+pV5TvTmdnNZeR8hbxMzMjBKvaWVO09PTiEajyrymgNCmio5PzmBdzKPEa2qlP2WzWfT19Sn1mlTMqZnXVIuoZxGtEGIPgA8B2AutOAMAAUBKKdecdymEuAfArVW+/ICU8kUV/s7HADwnpfxHIcSHAfillL+24uvPAniflPKrtZ5779698umnn77k81e+93/wxuvW472v2b1W88kC39h3Dr/xxafwvd++BduHqu/UNjMzg/7+/ja2jNpJz/fQxBJe8Q/34yM/cw1edeWI1c2iOv3pfz2Lbz87gSff87JLvsa+qzY35/vI8Vm86Z8fxr/94o140Tb1fgaqZfvEqTnc9dGH8OlfuB63XT5odXMsp1q+dIEQ4gkp5XWVvlbvCOEXAXwV2vmDqUYbIKW8rdG/A61tW0v/fwDA/9K/IISIlr52oMLfW1OuUMRyJo9uRRd8q6A3qmXDw2IJ4JRRp4oF/VU3lSFSlT5lVNWD6VWjryGstiMykRvUu8voMIA/k1Lul1IeW/nHiEYIIQaFEG8WQsSEEF4hxJ0A3gLg7tK3fA3AFUKIu4QQIQB/BuCZejaUqTREyou1/enZLKRqnw0UjUbb0RyyiJ5vPKNN6YkFK68JJnvqCPmQLRSRyV+6ex/7rtrcnK/qawhVy/bCGkIWhIB6+VJ96i0IPwPgrSa2QwJ4J4AzAOYB/C2Ad0kp/xsApJTTAO4C8MHS128E8OZmn0w/gJQFoX3p50MurnFYbD7PC7jK9Hz1UaZYkH3WSfRdYSuNErLvqs3N+eoFYaeiBaFq2V7YZZSH0wPq5Uv1qXf+1V8BeEgI8ccAJld+QUrZ6vmDesFXbY2h/j0/ALCj0ceudDD9YkqbhshD6e2ru/QP6Xyy9pTRTCaDjo7qawzJ2fR8L0wZ5Qihk5QLwkwefat2dWbfVZub811M5SAE0KHoFHfVso34vRCCI4Q61fKl+tR7tfoPACegTd1seA2h3ZRHCBW9e6eCSMALv1esOWWU3EFf28FzCJ0lxqlY5EKLqRw6Q/6aRyaRfXg8QjszldcpcrF6313tBdAnpXTcDh+V1hDOc8qo7Qkh0BUOlIv3ajjXXW0X1hByUxkn6lgxQrga+67a3JzvYiqn9PsLFbPtDPlZEJaomC+trd41hPcD2GVmQ9ppIckpo07QE/GXp/dWU2lKMKlDzzeRySPo88DvrfeSRXagjxBWWkPIvqs2N+e7mMopu6EMoGa2HSEf1xCWqJgvra3e2+0nAHxPCPE1XLqG8M8Mb5WBKq8hzMGj8Px+VXRH/GuOEKZSKd7NUpiebzyTL+8ER84RqzFCyL6rNjfnq3pBqGK2WkHIEUJAzXxpbfW+w4oA+BaAAIAN5jWnPeaTWXSFOb/f7rrCAZxdcPySVTJAPJPndFEHKq8h5Ple5CKLqRzWdYWtbgY1IBb0YTqesboZRJap6x2WlPIXKn1eCGH7+VuV1hAuJHPo4XRR2+uO+PHcucWa3xOJRNrUGrKCnm8ik0c0wILQaTpKx4RUmjLKvqs2N+ebyOSV3gBLxWw7Qn4cn0lY3QxbUDFfWltTBZ0Q4kohxP+Fdm6g4yymcuhSeMG3KrrDfu4ySgC0EcIYp4w6TsjvgdcjEM+wH5N7JDMFzmhwmI6Qr+KNKyK3qLsgFEIMCCF+SwjxJICnAdwA4LfMaphRKq0hXEjmeOSEA/REA0hmC8jkC1W/J5lMtrFF1G56vnHF77irSghtO/dKb7TYd9Xm1nyllEhk80qfmapith3cZbRMxXxpbTULQiGEXwhxlxDiGwDOAvgVaGcRLgD4KSnlV8xvovHmk1lOGXUAfVH+IkcJXS/BO+6OFQv6EM9Uv6lDpJJUroCi5BE5TtMR8iFbKCKd47WK3GmtEcJJAB8H8DyAm6SUu6SU7wfgmPMIK60hXExyyqgT6Oc41dppNBzmwn2V6flyhNC5OkK+ilNG2XfV5tZ8E6WbH9GAuiOEKmar72LNUUI186W1rVUQPgOgG8CNAK4XQvSY3iKT5QpFLGfy6A5zhNDu9IxqFYSVCn5Sh55vPJ1HTOEpWCrTRggvfZPFvqs2t+abKP2uqzxCqGK2FwpCzkhSMV9aW83UpZS3AdgK4HsA3g1gojR9NArAEUNsq9cQ6tMPuzlCaHsXRgirD0gnEtwVTGWJRAKFokQqxymjThWrslkD+67a3JpvIqt+QahituUdkXlEjpL50trWvA0gpTwlpXy/lHIbgNsBnAdQBLBPCPE3ZjfQaPpoEwtC+9PXEHKnUXfT32BxyqgzxYI+nkNIrnFhyiivV07CKaPkdg2NC0spfyylfAeAYQC/AeBKU1ploNVD34spbbSpm5vK2F5PVMtoscaU0WAw2K7mkAWCwWB5dIkFoTNV286dfVdtbs33wpRRdae4q5htjFNGy1TMl9bW1ERhKWVaSvlFKeUrjW6Q2cojhDx2wvaiAS98HoH5GlNGfT4WCSrz+XyuWJOjsmprCOvpu/FMHucWUmY0i0zm1muzG6aMqphtZ0h7T7jEEUIl86W1Kb9ydPUawvlSQchjJ+xPCIHuSO3D6TnXXW2JRKJcTPBgemeKBf1IZgsoFOVFn6/Vd1PZAv7mu4dw81/ejdv+9h48fnLO7GaSwdx6bXbDDSwVs+WU0QtUzJfWpnxBuJq+QQmPnXCGrrC/5pRRcoZcoYhj03Fk8o2f8VQuCBV+g6WycED7Z6aR873+6UdH8ZF7juHF2/qxvjuMX/rs4zg6FTeriUSG0c/cjHENoaPo/75Umt5O5AbKF4RCiIs+Xkzl4BFAB99cOkJ3JICFVPUpo4EAR3qd4A+++gxu/7t7sevP/gf/+wtPQkq59l+Clm/5jjvfYDlSyK+tpVpdEFbru9l8EV96bBx37BzER37mWnz6F26AzyMa+r0h67n12pwsXa8iCq8hVDFbn9eDSMDLNYRQM19am/IF4epNZeaTWXRHAvB4RJW/QXbSE/HXPIeQFy77+/rTZ/GfT57FT1+3Hq/fO4pvPnMePz46U9ffDQQC5TvuHZwy6kghX6kgzF88fb9a3/3ecxOYiWfwMzduBACM9UXwe3dejkMTy3jy9Ly5jSXDuPXaHM/mEfB54Peq+/ZK1WxjQR+njELdfKk2da9YJYXCxXelF5I5bijjIF3hQM2CMB7nNDI7O7eQwp9+bT+u3diDv/jJK/EXb7gCQ51B/NOPjtb19+PxOOKlO7Yqr8lRWdBfecpotb77+YdPY31PGLdsHyh/7ieuWodowIsvPjpuXkPJUG69NiczBeWnt6uabUfIh+UMRwhVzZdqU74gXG0xleP6QQfpjvhrHkxP9vbZh04hmSvgQz+9Fz6vB0GfF7/84i14+PgcnjhV30YhiWzpXC+Fp2CpLOirPGW0khMzCTx0fBZvuWEM3hWzOKJBH167dx2++cw5LHFKF9lYIpNHJMBrlRN1hPwcISTXUr4gXL2GcCmVQ0eIBaFTdIf9SGQLyK6abqbj1Ab7KhYl/vvps7hlWz/G+iLlz7/1xjH0RPz41/tPrPkY2pTRPPxeUS4syFlC5RHCtaeMPnJ8FgDw6itHLvnam68fQzpXxNefPmdCK8lobr02xzN55UcIVc22I8Qpo4C6+VJtyheEq9cQxjN5rkVyEH00d7HK0RM8QNW+Hj05h3OLabz+6tGLPh8J+HD7ziE8cmJuzU1CgsEgUtkCItxQxrH0TWUyq0YIK/XdA+eW0BH0Yaw3csnXrlrfhcuHOvCNfSwIncCt1+ZktqD8CKGq2WoFIWcgqJov1aZ8Qbh6DWE8k+cOow6i32lNVDjYGuBcdzv7r6fOIhLw4mW7hi752p4N3ZhLZHFmvvah4/G4dlRF0Kf8pUpZ5V1G82uvIXzu/BJ2ruusuOmXEAK3Xj6Ap08vIJVt/PgSai+3Xpvjmbzy651VzTYS8PHaAnXzpdpc9y4rnlb/Yq2S8tlAVQpCbkNvT+lcAd969jxesXu44ujenvVdAIB9ZxZqPo6UEplcsbwxCTlPtSmjq/tuoShx8PwSdo10Vn2sm7f2IVso4olT3G3U7tx6bU64YMqoqtmG/V6kGjgvdaUz80k8P7FscIusoWq+VJvy77JWriEsFiUSWfV3AFNJLFS7IPT7uR7Ujh4+PovldB6v2buu4td3DHci4PXgmTOLNR/H7/cjky9y/aCDhapsKrO6756aTSCZLWDXuuoF4fWbeuHzCDx0vL5jS8g6br02J10wxV3VbMOB5grC5yeW8dr/9wDu/If78Dv//jSmltMmtK59VM2XalO+IFy5hjCR1YoKriF0jvIIYZWF3pzrbk+PnpiDzyNw4+beil8P+DzYta4TT48v1HycYDDIKaMOd+Fg+otHCFf33efOLwEAdtcoCGNBH65a34UHj80a3EoymluvzdqmMmrfwFI125Dfi3SuiGKx/hGyo1NxvPVfHobfK/CLL9qMb+47j1/93BOOHmVTNV+qTfl3WSvXEOqjTBwhdI61powmk8l2Nofq9NjJOVwx2lXzTvme9V3Yf3YRhRr/+CaTSWTyxXJRQc6jTxnNrFpDuLrvHji3BL9XYNtgR83He8HWfjxzZrHqNYHswY3XZimlduyE4u8xVM02rG+AVWVX80r+7nvPI1+U+OIv34T3/MQuvO+1u/Hk6QX86Pkps5ppOlXzpdqULwhX0keZuIbQOdaaMlos1n/hpvZI5wrYN76IG6qMDur2bOhGMlvA0anqC9iLxSLSOY4QOlm1EcLVffe5c0vYNtiBwBpZv2BrHwpFicdO1HeOJVnDjdfmbKGIfFEqf9NZ1WzD5fXO9U0bTWbz+NHzU3jtnnXYMhADAPzUdesx1hvB3/7P4YZGGu1E1XypNuXfZa1cQ7isjxByyqhjdAS1uezVCkKfj1nazb7xBWQLRdywae2CUP/+anw+X2kNofKXKmXp2a1+k7W67x44t1Rz/aDumo09CHg9ePg4p43amRuvzYmM9jseVfzYCVWzDZdyq3cd4T3PTyOdK+KVVw6XP+f3evCuO7bhufNL+O6BCVPaaTZV86XalH+XddEawlJRwWMnnCPk98Ajqq8hDIVCbW4RreXRE3MQQtsApJbNfVF0BH149mz1jWVCoZC2yyg3lXEsIQSCPs8lx06s7LvTyxnMxDM1dxgt/z2/FztGOrD/XO0Nichabrw26+8xVJ8yqmq2+myGegvCbz97Hn3RwCU3P1+3dxSj3WH8xxNnDG9jO6iaL9WmfEF40RrCNEcInUYIgVjQxzWEDvLoyTlcPtSBrkjtnco8HoGxvgjOzFfPUFtDWOCxEw4X9HmQWTVldGXf1X8HNvVfeiB9JbtGOvHcuSVHb9ygOidfmyeX0vjOs+dxeLKxYwT0jetUnzLq5GxrKReEdZxFmM4V8MNDU3j57mH4vBf/++T1CLx89xB+fHSm6hnKdqZqvlSbq95l6VNGo4pvCa2ajpCfawgdIl86I26t9YO6ka4QJpYyVb9eLBa1TWU4Quho2u59F7/JWtl3J0u/A4Md9d2Z3rWuE/PJHCaWnL29u8qcem3+wDefw41/cTfe+fkn8XOfeKShzYv0N/+q71Pg1GzXEvZXPiKnkvsOTyOZLeDVV45U/PrLdw0jmy/ivsPThraxHVTNl2pzVUGojxDy2AlniQa9VaeMrpwSTNY7Oh1HMlvANWM9dX3/UGcIE4upql/3eDzapjIcIXS0SgXhyr47XTq3a7Czvu3O9amlz51bMqiFZDQnXpsPnFvEJx44gdfsWYcPvWkPppYz+IfvH67777tlDaETs61HI2sInzy9AL9X4MYtlW9+Xr+pB90RP7733KShbWwHVfOl2pRP3eu9cGF2y9071dSaMhqJ1DfFjNrj+QltitXOOtaCAdoI4XwyV/WObCQS4aYyCgj5PZfsMrqy704tZ+ARQF+0voJwBwtC23PatVlKiQ9+6yC6w3584PVX4CevXo+33DCGTz14Eocm6vs9c8t7DKdlW69wlR2RKzk6tYwt/TH4vZX/bfJ5Pbh9xxDuPjiJXMFZI26q5ku1Kf8ua+XQdzyTR8jvqdqByZ5iNaaMptOcMmYnB88vw+8V2DIQrev7h7vCAICJxco5ptPpUkGo9h131YX83ks2lVnZdyeX0uiPBeH1iNV/taJY0IdNfZHyYfZkP067Nv/o+Sk8eGwW77pjO7rC2vrn37/zckQDXvzLfSfqeoy4S5alOC3bejWyqczhyTguG4rV/J6X7x7CUjqPRx12RI6q+VJtyldGKzcdWM7klV/sraKOGiOE+bzzFmyr7NDEEi4b7Kj7pstIl7ZmrNpasHQ2h0JRcoTQ4UK+S6eMruy7U8sZDHU2trPdrnWdLAhtzGnX5i89Oo7hzhDeeuNY+XPdkQBesLUfj56s74iTZGkzkmhQ7RtYTsu2XiH9HMI1NpVJZQsYn09i+2BHze978bZ+eD0CDx1z1hE5quZLtbnqXVY8zYLQibiG0DkOnV/GzuHa/0iupBcB1UYI86UBfq4hdLZghSmjK/vu1FIGgx31TRfV7RrpxKnZJJbTOUPaSMZy0rU5lS3gviPTuHP30CU3s67f3IvxuRTO11jrrIu7ZMqok7JtRLjOEcJj03FICWxbY4QwEvBh50gHnjw9b1gb20HVfKk25VNfvYaQR044Tyzor7p1M+e628dCMouJpTR2jNRfEA6XRgjPVykIPX6tSNCn8pAzVdpU5uI1hOm6N5TR6YfYH5po7GgAag8nXZvvP6IdMP7y3cOXfE0/Y66eaX+JTB5ej1B+RoOTsm1EvZvK6MeRbF+jIASAqzf0YN/4AgpF5xyRo2q+VJvaVy1cvIaQU0adKRbyIZ7No1jhgprJVD+ygNpLf2N++XB9G8oA2lqwjpCv6k6jy0mtUFT9DZbqQn4vMvmLRwj1vpsrFDGbyGKgziMndPrGRQc5bdSWnHRt/t5zk+gM+Soel7NzpAPRgBePnVy7IExmC4gGvBCivrWwTuWkbBuhH2+01jmER6bi8HsFNvatvVb+mo3dSGQLDZ9paSVV86XalH+XtXINIaeMOlNH0AcpgWSFu3a5HKeL2cWh0hvzRqaMAvpZhJVHCBPpLABwUxmHC/k8l4wQ6n13Jp6BlMBQgyOEw50hRANeHJ9OGNZOMo5Trs35QhF3H5zE7TsvnS4KaLtFXrOxB4+dWHvaXzyTV366KOCcbBvlKY3urt4Aa7Ujk8vY3B+ta628fgSTk6aNqpov1aZ8QbhSnCOEjqT/A1tpHaHqd2Kd5NDEMnqjAQw0uBZMO4uwckGYLWg3dDhC6GyVRgj1vjvV4KH0K//+xr4oTs2yILQjp1ybHz81j/lkDi/fNVT1e27Y1IvnJ5exkMzWfKxk1h0FoVOybUY44F1zU5nDk3FsW2NDGd1YbwR90QCePLVgQOvaQ+V8qTrl32VxDaHz6ZlV2mk0Flt7Dj+1x8GJZewY7mj4H5ORrlDVNYTegFZcclMZZ9POIbz4TZbed6eW9YKwsRsJALCpP4KTs8nWG0iGc8q1+aFjs/AI4EXb+qt+z/WlqaSPn6w9ypPIFBBR/FB6wDnZNiPk89ZcQ6jvMLrWhjI6IQSuHuvBUw4aIVQ5X6pO+XdZl64h9FvYGmpGR7B6Qci57vYgpcThiWVc3uB0UUA7i3A6nql4eO9yUss3xCmjjhYsHTuxcgq/3ncnS9OFGz12AgA29UUxPpdE3mEHP7uBU67NT40vYPtQBzpC1d8b7N3QDQA4cK72etVsvuiK2QxOybYZ4YAXqRoH05d3GK1zhBAArh7rxvGZBOYTtUeY7ULlfKk65a9c+huQbL6IbL6ImOLnA6mo1pTRbNYZF1jVTS1nkMoVsKW/vgPpVxrpCkFKYHr50n+EkmntcxwhdLaQ34OiBHKFCwWh3nenljMQAuiPBRp+3E39UeSLEmcX1j4SgNrLCdfmYlFi3/gCrh7rrvl9Ib8XAx1BnF2oPRqdyRdcsd7ZCdk2K+T31txU5lRpRsLmBv6t03+/njm72FLb2kXlfKk617zL0o8t4BpC54nVGCEke9D/kRyrY9e11YY7qx89kcnrawjVf5OlMv3YkEqbNUwvp9EXDcBXxwYNq20q/b6dmOE6QmrcidkEFlM5XL2hZ83vHe0Or3njIVsoIuCCEUKVhStMb19pJq7dpGxkrfzO0s7bh3lEDtmY8lcufQ2hXkzEakwLIXvq4BpC29M39tjY2/j5RfpZhJU2lvH4tFEjN0zDUllQLwhXvNHS++7kUqbhDWV0m/q137eTLAhtxwnX5qdOLwAA9q4xQggAoz1hnJ2vXRBmcu6YMuqEbJsVDlx6ZupKM/EMPALojdY/o6EnGkB/LOiYoydUzpeqU/7Kpa8hXE5zhNCpyiOE6Uu3QubUBns4NZuE1yMw2hNu+O+OlA+nv/TNViLDYydUECq9Sc6sWJtzYcpo44fS6wZiQUQDXm4sY0NOuDY/PT6PjqAPlw2s/QZ4fU8Y5xbSFc/D1bllhNAJ2TYr7K+9qcxMPIPeaABeT2Obp20fiuHwVLzV5rWFyvlSdcpfufQ1hHFOGXWsaI0po7xw2cOpuSRGu8N1ncu0WlfYDyGAxdSlBX/5HEKuIXS0UIURQr3vaiOEzRWE+tETJ3n0hO044dr81OkF7NnQDU8db+7Xd4eRLRQxHa++4UY2X0SgiWug0zgh22YF1ygIp5ez6I81fr3aPtSBo5PLF22sZVcq50vVqX/lKimvIeSxE44T8HkQ8HkQz9Q+G4isc3o2gY19jU8XBbQ39bGAr3LBX1pDyF1Gne1CQXjx7n2FosRsvPkpo4C2ucMpjhBSg1LZAg5NLJd3EF2LPvvhTI1po5l8kTevHC7sr30O4Wwi01RBuG0ohkS2wA2wyLaUv3J5PNpLXOYIoaN1BH2IZy4dQYpGG9/EhIx3cjbZdEEIaKPAlXaRlR6tv/JNlrOFSvmt3FQmGo0imc2jKIHOcPPX5U39ER49YUN2vzYfOLeIQlHWXxB2a9e3Wm/otRFC9W9e2T3bVtQzZbSviR2Rtw9px1QcmbT/tFGV86XqXPMuS3+z2cERQkeqVjDk89x51GqLyRwWUzls7G3+H5FYyIdE9tIs06XPuWEalsoqTRnN5/NIlu7ERwLNX5c39mlHT9QauaH2s/u1+fnSBh8713XW9f36CGGtjWWyeXesIbR7tq3QziGsURA2OWV026C2TtUJG8uonC9Vp/yVS99URh9dinKE0JFiQV/FKaM8QNV6p+a09VtjLY4QLlco+JOZLAJeT11rfMi+9Cm/K6eMZjKZckEYbeF8WP08MK4jtBe7X5uPTsURCXixrqu+6cqxoA9dYX/VswiLRYlswR27jNo921aE/F6kc8WKa/0SmTxSuUJTBWF3JICBjiAOO2CEUOV8qTr1r1wl8UwBQgARv/rTOVQUC1WeMkrW03d4bGXKaEfQV17nu1ImL13xBkt15Smjq+6865m3MkK4rlsbual0jiVRNUen4rhsMAYh6r/ZNNpd/eiJbGnKshtGCFUWLr1HzOQvnYKun0HY38SUUUDbafTIlP1HCMmdlL9y6WsI4+k8YgEfRxocSltDeGnBwLnu1jtdGpkZa+IMQl006EWiwghwUXjKZ9iRc1WaMqqtISyNELZQEA52BOERLAjtxu7X5iOT8bqOm1hptKf64fR6AeGGG1h2z7YV+s2rVIWNZcoFYZO7Im8b7MCRyXjNo0vsQOV8qTr1r1wl8UyO00UdrNoaQn1KMFnn1GwSgx3BlkZ5YkF/xYI/nSu44g2W6vQMV951LxaL5XWjkRamjPq9Hgx0BDFR4RxLso6dr83L6RwmltK4bKjBgrA0QlhpOmHWRQWhnbNtlT5CWGkd4UxcO45hoIkpo4C2sUwqZ/+dRlXOl6pT/sql/2KnckVEAhxpcCptyuilF+hUyt4XVjc41eIOowAQC3orFoTJTI47jCogWGGEMJVKIZlpfYQQAIa7whwhtBk7X5uPlg4Ib3SEcH1PGIlsoeKZqW6aMmrnbFsVDtQqCPUpo80VhJtK/06Oz9n7mByV86Xq1L9ylWRyBVdcqFUVDXgrrjEj651dSGFDT4sFYUibErz6znu2IBHkGYSOp0/DWr0upzxC2OLNupHOEAtCqtuRUkG4rXQUQL1Gu6ufRZgpFRC8XjmbPr294pTRZW2EsDfa3BrCDaVlFePz9i4IyZ2Ur5D0NYTpfLHc0cl5Qn4vMvnCJQVDJNJaIUKtKRYlJpfSGK5zp75qokEfCkV5ScGQL7pjCpbqAl4PhLh4hDASiSBZusnT6nT+4a4QJlgQ2oqdr83HpuII+DzYUDpKol760RPnKkz5c9MIoZ2zbdWFTWUqjxB2hf1NZzzSFYLXI3Da5iOEKudL1blmUR3XIjlb0OdBUQK5gkTAV9/GQCdnEvjiY6fhEQLXbezB7TuHTG6l+8wkMsgXZcsFYaxUECyn8xfduMnwRo4ShBAI+byX7jJaPoewxRHCrhDimTyW0zl0hPwtPRap78hUHFv6o/A1eL5pT0QbGao4ZbR0M4tnpjpbecpotvIuo83uMAoAPq8H67pDGJ/jlEyyH+WvXPoaQr6xdLZQlbt2yWT1O21/9t8H8M/3Hce/3Hccv/zZx7H/7KKpbXSjyUVtTcVQpzEF4eppwalsnlOwFBHyey46hzCZTCKZzcPrES3frBspTeXjKKF91Lo2W+3I1DIuG2xs/SAAdIS069RShQ3OyruMumDNs52zbZV+Zmq1NYTNrh/UbeiJ2H7KqMr5UnXqX7lKMrlCeR0LOc+FTSnq2/3qiVPzuO/wNP7wFTvwxJ++DD2RAN7z9f223+7ZaSaWtDfgIwZMGQVwycYy2hpC9lsVaAc+rz6HsIBIwNvQWXCV6L9/51gQ0hpS2QLOzKeaKggvzGTgCKGqwoHSsRMVCsLZeLbpIyd0Y70RjhCSLSl/5dLXEGbyRY40OJheFKx+QxkOV14D8uG7j6A3GsDP3bwRXRE//uhVO/HU6QV85Ylx09vqJvpW/8MtjhB2VCkIcwXJcwgVEfJ7kV6xRjQcDiOZzbe8wyhw4fePR0/YR7Vrs9VOzSUgJbClwR1GAW3KXzTgxVLq0hHCckHoghtYds3WCOUzUytsKjMdzzR95IRuQ28EM/EMkln7bpKncr5UnfpXrpI0Rwgd7cKU0YtHCPWCf6VnzizgvsPTeMctW8pn4911zSiuHuvGx+49XvEMKWrOxFIaXo9AX4v/SEarTBnNFIocIVRE0Oe56IaOx+NBIlto6QxCnT5lmTuN2kela7MdnCmNzjS6oYyuI+SvOEKoL2dww41nu2ZrhGrnEKZzBSyn8y2tIQS0o0uAyjvV2oXK+VJ1yqeuryHUNpVR/0KtqlCVEcJEInHJ9977/DQA4C3Xj5U/J4TAXdesx4mZBA5Pxk1sqbucX0xjqCMIr6e1KX+xUOURwnSWm0GpYvWU0UQigWQmb8j5sAGfB/2xINcQ2kila7MdnCmt31rf5FE5nWEflmusIXTDCKFdszWCvqnM6vcaswntyIlW1xCO9dr/LEKV86Xq1L9ylWibyrjm5SonWGMr6NX2nVnEloEouiIX7zb48t1DEAL47v4JU9roRpNLaQy1uH4QuLA259I1hNwMShUhvweZVWuAk9lCeRS/VSNdIa4hpDWdmU8h6PM0PdLTEfJjqeIIYWlTGRcUhCqrtqnMQlIrCLsjrY0Q6mcR2v3oCXIf5a9cHo8HUsrSlFG+sXQqfYRw9RvKYPDSu3XPnFnAnvXdl3x+sCOE6zb24Dv7z5vSRjeaWEy3vH4QWLGpzKo775k8N5VRhbaG8MKbrGAwiGS2gKgBI4SAVhByDaF9VLo228GZ+RTW94Sb3sioM1R5hDDrooLQrtkaweMRCPg8FaeMAq0fkdMXDSDs99p6YxmV86Xq1L9yQduYoijdcaFWVXmh96oRQp/v4tGFicU0ppYzuGp9V8XHuXP3MA5NLOPkDKdEGGFisfVD6QEg4vdCiIvXEBaKEvmi5FRvRaxeQ+jz+ZDI5hFp8VB63UhXiGsIbWT1tdkuziwkm54uClQfIXTTpjJ2zdYoYb/3kk1lkqWPwy0WhEIIbadRGx89oXq+VJnyV65isVieZsgRQucKVTl2YvVc92fOLABA1YLwFVcMAwC+w2mjLVtO55DIFgwZIfR4BKIBH+KZC/8IZ110rpcbaGsIL/RfbQ2hcSOEw11hLKfzl0w7JmvYdR2SPkLYrI4qI4QXpoyq/z7DrtkaJez3XjJCWC4IDXgfuaE3zDWEZDu2fKclhNgmhEgLIf5t1effKoQ4JYRICCH+SwjRW8/j6W9COELoXHp2a60hfObMIrwegV0jlQvC9T0R7BjuwIPHZgxvo9tMls4gNGKEENDWEcYzF+6866NJ7LdqCPo85SJfl8jmDV1DCPBweqpuOZ3DQjJXXsfVjM6wtsvo6t2q3TRCqLpwwIvUqpvPRk0ZBbT3IeNzSe54TrZi1yvXPwF4bOUnhBC7AXwcwM8BGAKQBPCRtR5ICHFhO2iOEDpWtRHCQODiBd77zixg+1BHzWkdV4/14OnxBR5S3yJ9et6QASOEABANepFYMUKo33HnyL4aPEJA4kKf8/v92hpCA46dAIC+0iYhs/GMIY9HrVl9bbaDswvauq1WRwhzBXnJv0XZQgFej2h5x2UnsGO2Rlq9IzJg3JRRQPv9S2QLWLbpbAbV86XKbFcQCiHeDGABwN2rvvQzAL4hpbxPShkH8B4AbxBCdNR6PI/HU75w842lc+k7xK6+SK+8cEkp8ezZReypMl1Ud81YN5bTeRyb5vETrdBHYkaMGiEM+S/6B/LCuV62u0xRE4QQuOgejMeHQlEaNkLYF9U2QpgrbQ9P1rLjm0r9DMJW1hB2hrTdq1efRZjJuefMVDtma6SQ33PJe41UqSCM+Fu/Xg10aNeqqSV7zmZQPV+qzFZXLyFEJ4A/B/A7Fb68G8A+/QMp5TEAWQDbaz1moVDg1DMF6OsyVh9MH49fKOpOzyWxkMzhqgo7jK509VgPAODJ0/PGNtJlJgweIYwFvRdtKuOmNTlu4BG4aIrU9PwSABi2hrA8QsiC0BZWXpvt4sIZhK2NEAK4ZGOZbKHomumidszWSH6PB/nCxTOI9DWFoUDrGev/Zk4u2XM2g+r5UmV220ro/QA+IaU8U2FL6BiAxVWfWwRwyQihEOIdAN4BAOvWrcNyUnvjmk3GMTMzg2g0inw+j0xG64zRaBTFYhGplHb3MBLR7h4mk9o/HuFwGB6Pp7zQNhgMajvklT4OBAIIBALlThQIBBAMBhGPxyGlhN/v17ZYTyZRLBbh8/kQCoXKH3s8HkQiEaTTaeTz+fLHmUwGuVwOQgjEYjFkMhlks9qbnVgshmw2W/5Y9ddULL2RXE6kMTMzU35N6fSFjw+e1V7bYLCAmZmZqq+pU6TQGfLikWPTeP1VQ8ypydd0cmoBXSEfZD6L5XTrr8mPIiYSaSwtLSEQCGByeg4AUMilkclkmJPDX1Mul0WhKDE3N4disYjpBa0gRCGLmZmZ1q8RBe0Gwvn5+EXXCOZkzWtKJpPlHOzymo6en0fQ54HIxJH2yaZyklmtzdOLCQyFUX5NyXQWfo9wxe/e4uKicq9pZU4CRaSzF7+PmFlYhlcA6UQcsvQamn1NXQHt/e2xczPY2Wu/a0QikUBHR4ftc1Lxd8/s11RL2wpCIcQ9AG6t8uUHAPxvAHcAuLrK98QBdK76XCeA5dXfKKX8ZwD/DABXX321lEK7Az3Y14P+/r7y93V0XFxLRqPRiz7Ww9KFw+GaH4dCF4+UrD7LZfXXG/14rccD1H5NAZ8HBeFFf39/+Wv5fB6dndqvxdKJcQDA5WND6F+xaUCl13T1WC/2n48jGAwypzo+rvR4i1mBke5wuS2tvqbezgiOzKTLeYZi2uP1dMaYU50f2/k1hYMTkAB6e7W9wE4taCMsA92dF/XpVl5TR8iHeFZe9HhmvqZmP7ZzTs1+vPrxuru7y31ZZ/VrmklJbOiNoK+vr+LX63m8DUPaLIas9KKjo6P8mgo4g1DA64rfvYGBgYuyVeE1rcwp4PchV8RFWQpfEOGAD11dXU21YeXHgaj2O5SU/vL10E7XCL3QsHtOlV6D03/3APNfUzVtKwillLfV+roQ4l0ANgE4XRodjAHwCiF2SSmvAXAAwJ4V378FQBDA4VqP6/F4ymfXcVMZZ1t9jhlwcUeYKM3HH+xc+1DVa8Z68A93T2MpnSuvCaHGzCYy6I8Zd4CttsvoiimjOU4ZVYkQ4qKNnPLQco0YtKkMoB36zCmj9mDHw621Mwibny4KaOcQAsBSatWU0XwRAa87pozaMVsjeT0CheLqKaN5QzaUAbR/62JBX3mnbrtRPV+qzE5Xr38GsBXA3tKfjwH4FoA7S1//PIDXCCFeLISIQltr+J9SyktGCFcqFArlN5YhnmfmaCG/t+YawomlNHqjgboKiGs2dkNKYN/4gtHNdI25RBY9UeMWn8eCPiQy+fI6swvnh7LfqsAjBFbusj67qPXdqEGbygBAXyzITWVswo7rkFo9gxBYuanMxTtEZvIF19y8smO2RvJ5BPKrC8JswZAjJ3SDHUFMLXMNIdmHbd5pSSmTUsoJ/Q+0KaJpKeV06esHAPwqtMJwCtrawV+r57HLI4QuuVirKuT3ILNqhHDlJhVTS2kMdtR3Z2vPhm4AwNOnF4xqnuvMJbLoM7AgjAZ9yBdluejnpjJq8QiU1wIDQDKrvaE28k1WbzTAgtAm7HbGWipbwEIyh5GuVkcIK28qk8m7Z1MZu2VrNK9HXLKpTDJbMORQet1gZ9C2u4yqni9VZrdNZcqklO+r8LkvAPhCI48jhOAIoSKCPm+5uNf5/Reme04spes+JL0z5Mf6njAOT/FOWDOy+SKW03n0GlgQ6m+04pl8aTSYuwOrxOO5+NiJbFHbWCEaNHCEMBrA0xz1t4WV12Y7mC6NxtR707CaSMALr0dccuxE1kUFod2yNZrP40G+ePFspFSuYNiUUQAY7AjZ9lqler5UmfJXL+0cwtLUM440OJo2QnjxRfqiNYSLGQw3cATCtsEYjkzWnHFMVcwntVEYI6eM6lMH9aMn9PNDg7yRowSxaoQwK0sFoQkjhMUi73BbzW7rkKbj+hrz1o7JEUKgI+SrMGXUPecQ2i1bo/m8FdYQGjxCONQZxNRy2pajcarnS5Upf/UqFApI5/nGUgWhCiOE+na9uUIRs4lMQ2fibR/qwPHpBPKF4trfTBfRp+UZPWUUuLA2J1vqt27ZqEF1q9cQLpbeoEcMHCHsjQZQKMpLpvNR++nXZruYKp35NmDARlgdIV/FTWXcUhDaLVujeSusIUwavoYwhHSuiKVVNxbsQPV8qTJXXL24W6EaQn5vedRIVyxN65hezkDKxg5Jv2wwhmyhiNNzvPg1Si8IzZgyqo8Q6ndovZ5LziQlB1q9hjBRWkNo5F13fddb7jRqvWLRXjfa9A086tmFei2dIf8lI4RuOpjebtkazVdhl9F0roCwgRtg6b+H08v2W0eoer5UmfJXLyEE0vkC/F7BN5YOF/R5yuvKdD6fdoHWj5wY7qr/H/vtQ9rZMIcnuY6wUbMmFIT6CKF+9IRePHjYb5XgEeKigjCdlwj5PYZel/XfR24sYz392mwX08sZeD0CvZHWr1kdIV+FTWXcs8uo3bI1mtfjqThCGDZwlpl+83pyyX47jaqeL1WmfEGoryHk+kHnqzRCqB+4ObmoFYSNjhACwNEpriNs1LwJBWGsdB5dIqsV/eURQsGCUAVCXLqpjJFHTgAXfh9n4ywIrVbvYcjtMrWcRn8sYMgNpo5KI4QuOofQbtkardIIYSpXQMTIEcLS5kZ2PItQ9XypMuWvXoVCQVvszUPpHS/ov/Rgen2uu35RbaQgjAZ9GO0Oc4SwCbOJLIQAusPG7Ubm9WiXo0JpukpBcsqoSvQY9U0UlpIZQw+lB4C+GEcI7cJu65CmljMY7DDmjW7FKaP5omv2KbBbtkbzegRyq/YWSGULCBl67IT2u2jHswhVz5cqc8XVK50ruGaxt8qCvksPptfnuk8sZeD3Nj4daNtQDEd49ETD5hNZdIX98Bl4R1wfCdT/HdZ3ivRwhFAJeo76jfdktmDiCKH93mS5jd3WIU0vZzDQ4pETukqbymRcNEJot2yNtnqEMF8oIlsoGrqpTCzoQzTgteUIoer5UmWuuHpl8kWeQaiAUIURQk9pVGlyKY3BjlDD04G2D3Xg2HT8kukhVNtcImvodFEAKEVZLgT1wpAjhGrQY9TXEaZyxr7BArSbRh1BHzeVsQH92mwX2gihMQVhZ9iPeDZ/0fEmbjqH0G7ZGs3nvXgNYar0vsPIDbAAbUbTlA3XEKqeL1WmfOperxeZnLFD/WSNkN97yTmEkUgEgFYQ1nso/UqXDcaQzXOn0UbNJjKGHjkBXCj89Kmi+n9ZD6pBlEcItVzTBWnoofS63liAU0ZtQL8220GhKDEbN26EsDPkg5RAPHthR+R8UbpmUxk7ZWuG1SOEqdK6diMPpge0nUanbLjLqOr5UmXKF4TFYhHpnHvOB1JZ0OdBtlC86K5sOq1dTCeW0hhqYjvxCzuNcmOZRswncugxYLe+lS5MGdXyLRYlPOJCIUHOpk8Z1TcaTWTyho8QAhcOpydr6ddmO5hNZFCUMGyEUD8iR582Wj4z1SXvM+yUrRm8pYJQlmczaAWh0derwY6QLXcZVT1fqkz5q5eUEpk8RwhVoGe4ch1hPq/doZ1cTDe0oYxuc18UAHB6liOEjZhNZMsbeBhFn+5bXDFCyPWD6lg9ZTSZMXbXPl1fNMApozagX5vtoHwovWEFobaZlr6xjNsKQjtlawaf5+Kbk8msOVNGe6OB8o7ddqJ6vlSZK65eHCFUQ6iU4cp1hB6PB/FMHolsoamCsCviR0fIh/F5FoT1KhYl5pPGryGsNELokj0aXGH1pjIFKeH3Gl/wayOE9rvr7jZ2Woc0HdcLQmN2GdXfT+iFoH4+rlveZ9gpWzN4S9el/OqC0OARwp5IAMuZ/CU7mlpN9XypMuVT93q92jmEHCF0vGCFEcJIJIKFZOlMvCanMG7oiWCcawjrtpzOo1CUhk8Z9ay6K1soSniF8pco1xCrRgglhCkjwH2xIOYS2fJ0L7KGndYhTZdGCI2aMqrvrpwv6gWhu0YI7ZStGVaPEKZN2lSmJ6qNNC8kc2t8Z3upni9VpvzVq1gslnYZZUHodPpOsStHCDOZTPnuXbNnmm3oDWN8PtV6A11itjT6YvSUUW+lKaPKX6HcQ18LKkv3cwrFoinrQ3sifuQKEvEMpz1ZKZOxzyitvnGHUVNG/aVrVa6gXauypREet4wQ2ilbM+hn4uYLF48QGj3Fvbt0U1W/qW0XqudLlSl/9ZJS8hxCRYRKO7il8xcKwlwuV37j1+yOhRt6Ijgzn+SIQp30DTt6o8a8udJVOoeQO4yqY/UaQrPy1dd3sSC0Vi5nn1GP6eUMOkM+w24Ml0cISwWDvvu1W95n2ClbM/jLU0a1XMvHTgSMzbcnol2r5m02Qqh6vlSZK65eHCFUQ7A8QnhhyqgQAsmMdrFu9pDrDb0RpHPF8joTqq1cEBo+ZVT778oRQu4wqg7PqmMnijDnjEl9B0h9ww+yhp367pSBh9IDgK9UMORKBYM+QuiWKaN2ytYM3lVTRlOl40XCBo8Q6ssu5m02Qqh6vlSZ8lcvfQ2hW+7cqUwfIcysmDIai8VWjBA2P2UUAMbnOG20HuWC0Ogpo6s3lZGAj3NGlXFhhHDl58woCPUdIHmX20qxWMzqJpRNL2cwaNCGMgDg96weIdQ3lXHHjWc7ZWsGfQ3h6k1lIgYPLHRH9DWE9ioIVc+XKlP+3Za+hjDIEULH0zNMr9hURltDWCoImx0h7NEWUJ/hTqN1mWtxE59qVt+V5ZRRtZTXEOJCvmbciI6Vpo4vcYTQUnZahzQdz6DfhBHCfMGdI4R2ytYM+hrC8ghhzrxdRgH7TRlVPV+qTPmrl36Iub4hCTlXpU1lstksEi1uKrO+VBByp9H6zMWzCPu9hv/jKISAECumjLIgVMrqg+mLJp0z2dnilFEpJf7v/xzC2z71KPaNLxjYMnfJZu0z6jGfyKK3NBpjBH95ymhpUxl9l1GXnJNjp2zNsHqEMJUtQAjj14hGAl4EvB5Dpow+c2YBx6bjBrRK/XypMuNPBbYZ/c2lW6ZyqEzPcOWxEwCQKE0ZjTW5qUw44EV/LMgpo3VaSufQFTbuzdVKXiEuHDshWRCqZPWmMoUiTN1Uptkpox+99xj+6UfHEPJ78Lp/egC/efs2/M7LthvZRGqjQlFiKZ1Hl4EzGi7sQnnxsRNB3nhWwoXZKqVNZbIFhP1ew9fWCSHQHfFjIdHaCOG3njmP3/jikyhKYMdwB/72p/bgitEug1pJbqH81UuULtwcIXS+SiOEsVgMyUweQrR2RpB29ARHCOsRz+QRC5lzL8njESis2IXS5+WNHFWsPphewqw1hNrvZryJEcL/OTCBv/nu83j93nV47E/uwKuuHMZH7zmKcwu8WdQou6xDWkppb7a7DbyJVR5BKrhzhNAu2ZrFt+pYkWSugIjBM2J0PZFASyOE9x6exru+/BSuGevBe1+zC3OJLH7n358u/042Q/V8qTLlr17F0h2eEEcIHU/fKTazaspoPFNANOBr6e7dhp4IC8I6Lafz5TfdRvMKUZ7mXZDmjCCRNcoH05c3DZLwmBBwJOCF1yOamjL62YdOYlNfBH/zxj3oCPnxx6/aCSmBj997zPB2qs4u084WSgWhfgi4Efylwq+8y6jLDqa3S7Zm0Y8VKayYMmr0Egldd8Tf9MH0haLEH/zHM9g6EMMn3nY9fuGFm/EXP3klDk/G8a8/Pt50m1TPlypT/uqld2hO5XA+ff7+yimj2WwWyWy+5bt3G3rDOLeQLk8BouqW0/mmp+euxesRF51DKMCzIVVx6RpCcwp+IQRiQV/DU0YXklk8fHwOr7pypPzGfn1PBG+4ZhRffGy8fLg51ccubyr1HRy7w8ZNGb2wqUxpl9G8u3YZtUu2Zqm0hrCVGUi1tDJC+OCxGUwspfFbt28rL+O4Y9cQ7tw9hH+8+0jTG+X9/+29eZwk2VXf+zsRkUtlZmWtXdX7NkvPqhnNIg1CI41BSCAjBMh+FkhsDywbfYRtZIyxH2LHfnoYkB8IjHhgCWQZCSMkBEICGY2EFqQZzUzP0jPT090zvXfXvuUeEff9EXEjI7Nyr7hRmRHn+/n0TFVuEVk34+Y995zz+0V9fJnWRD5KkosPzhCOPjJD6C8ZBYBC1dpxgHJ4OgPLFri6zou+bmyWa8in1fQQattEZThFGBWafSaFIlEZAG5A2F+G8HPPLsCyBb79jr0Nt7/zoRthWjY+9JWXAjxDJixkhnAiSFEZ2UNoy4AwXhnCqNPcQ1isWYF7EEqmsomBVUb/7BuXkE8b+JZb5xpuf8933oaKaeNPH70UxCkyMSH6s5e74OAM4eiT0DXoGjUY02ezWRQq5sAKoxKpNHqZe4W6oj5DWBeVSfBGTmTYZkwv1Bkgj6eNvm0nPvvMNeyfSOPOJjGGo7NZPHB8Bp87tRDkKUaebDa726cAwJ8hDLCHsI3tRFz8jodlbFXR3CNarloYU7SGnMwksVasQoj+qmG2KiY+88w1vOmu/dsy0wenMnjg2Aw+dfJK368LRH98mdZEfvaSi480+xBGgpSheeU5AGCaphMQ7nD3bj7veFRd3+AMYTe2Kgp7CJtEZSI/QcUI8onKyD5CVT2i+XSir5LRYtXEF08v4vW3720ZpD50Yg+ev76Jq+u8YdQrpjkcPpCyP2syQJVRLyCUGcJavERlhmVsVdHsiVus7XyN0Y6pTAKmLbBV6e9v+tdPXUW5ZuN77znY8v7vuns/zi0V8PTljb7PKerjy7Qm8rOX50PImYZIkE7oDRnCSqWCQnXnGau5fBoAsLDBhqydMC0bxaqlTmW0QVSGewijhAz+hBDeRp2qktHxdH8lo188vYSKaeMNt+9tef9rb55zH7cYyPnFgWExt5YBYZBWObJktObLECZ0UiKSNIwMy9iqojngV9lDKDcq+hWW+czT13B4OoN7Dk+2vP877tiLhE74i5OX+z6nqI8v05roB4SCRWWiRNrQtvUQFis7l4QeTxkYS+gsHNGFQsX5248r6iFsKBm1hdd3xow+ftsJaT2hK1pAj6eNvnbcn7q8BkMj3HNksuX9N8/nsDefxhc4IBw51ks15NNGoJ81TSNo5BOVqdmxEZSJA9JnMgyV0Wk3IFwp9C7kIoTAyUtreMWx6bZl95OZJF578x586uRVb5OVYToR/eWWe7FwhjAapBJ6g8poNpt1fPF2mCEkIszlU7jOGcKObLhleKpKRjXylYwKgYSh5jhM+PiN6eVGnSrNoPE+S0afv7aFo7PZtot6IsJDJ/bg719YYiXiHhmWPqS1YjXQclGJoWue7UTNzRDGhWEZW1XUfQjrojLKfAhdO5R+lEavrJextFXFXQc7m89/58v249pGGU9eXu/rnKI+vkxrIh8Qyo0RzhBGg1RThtC2nRLGIOr758fT3EPYBZl1GVcoKmP7M4TxWWNFHvKJykidA2Uqo27JaK+CCi8sbOLm+c5mzK+9eQ82yyYev7gWwBlGH+kBvNusFmuYDFBhVJLQyMsQ1iw7VgqjwzK2qpAlo9aQlow+6c5Bdx6c7Pi4V90wAwB45MWVvs4p6uPLtCbyMxgb00eLdEJH2ZchLBaLbg/hzsd3Lp/CwiZnCDsh+7KUloxKnzobEPzFFBn8PoT1HkI1xxpPGzBt0dBv3I5S1cKFlSJunh/v+LhvvmkWRMBXzy4HdZqRplQaDgGetVIt0P5BiaFrDSqjiZgIygDDM7aq8PsQWrZAxbSVlYxOuQFhPxnCk5fWkdAJt+7rPGfN5dM4OpPB11/qLyCM+vgyrYn8DMYZwmiRTmio+DKE5ZoNIYBMABmr+byTIRxEpnlU+JtnruF1v/EFvP/zZ7A+gPfRVsV5jjpRmboQlC2Esh4zJnz8JaOWclEZJwDopWz0zMIWhEDXgDCfTuDYbBZP91l+xewu64pKRhM6oWbLDKGIjcJoHPD3EEpVc1VK9RNjCRChLy/Cpy6v4Za9+Z76Vl9xbBqPvLTCfYRMV2Izg/FkHQ1SRmOGUBiOXUQ2gN27+XwKxarVt/zzqHBmYRM/+dEnsLxVwa999nm84X1fRKlqdX+ij3qGkH0Imf7wi8oI9xJW5UOYdz+fvXgRnr6+CQBdS0YB4I79E3jmSv8y7nEkk8ns9ikAcDKEUwpKRg2tniGsmfHKEA7L2KrCnyGsmc73kao1pK4R8umE55fZDdsWePLSOu7s0j8ouf/oNNaKNZxZ3Or5nKI+vkxrYjODxUUOOuokDQ1VX0BYqDoLvmwAGcK5cdd6IoJlo8WqiX/xx99AOqHj0//6Qfz+D96Haxtl/PXTV/t6HbnAVtVD2CAqYwtlGSQmfKiFqIwqHQ65YdFLhvD0wiaSuoYjM92FFG7fn8fltRJW+1AEZHYP2xZYL9UCNaWXGHq9h7Bq2UgYPFdFhboPoY2K5WyaJhT2iE5lEj1nCF9aLmCzbHYVlJG84tg0AOBrffYRMvEj8gGhEEKZkh0TPgQ0lHSubBQAIBBRmbkIm9N/8okrOLtYwG/8s7uxb2IMr7t1DkdnMviTr1/s63W2Qugh9PsQeqkkZuSp9xD6fAiV2U44n89esv2nr23i+J5sTxmeOw44izDOEnanWCzu9ilgo1yDEMCEkpJRzVcyGq8M4TCMrUoaMoSWzBCqW0hOZpI9ZwifvOSUrL+si6CM5PB0BvP5VF/CMlEfX6Y1sZjBOMsQHZqHsuiWPO7UdgJwegiBaJrT/8UTV3BsNovX3DQLwCnV+2f3H8bXX1rB2T5KSTbLNegaIa2oJ9cRlZEqo+pER5jwaeVDqKpktJ4h7KVkdAs3dekflNy+Pw8AePoK9xGOAlK5UUmGUKO6qEzMSkajjuGOpWkJ1NyKJJUqsuOuKnIvPHNlHSlDw01z3UvcAWeOvf/oNL7+4kqk9RGYnRP9GYyIF5URgkDwz2kWOQu/TAAqozIgjFqG8PpGGf/w4jLedNf+hgX4W+49AEMjfOyR3rOEWxUT42lD2UJeo3oPoW0LJNmHMDJ4ojK28BYmquZmuUHUrWR0q2Li8loJJ3roHwScnfyDU2MsLNMDY2Nju30KWCu5AaGKHkJd87JHNcuOlU7BMIytSvSGDKETEKoM+HMpA4UetQsurpRwaDrjBa29cO+RKVzbKGOxx3aYqI8v05pYzGCqFq9M+BABAvWIsFRzfs4GUDKaSxnIJPXImdN/6uQVCAF81137G26fG0/joRNz+Msne+8j3CybgWRj26Fr5JUTWkJAj5HZc9QhX4YwPJXRzousMwtOdrzXDCHgZAm5ZLQ7mrb7ywtZhqdKZdT0jOlFrIzph2FsVWL4ewhN9QFhtp+AcLWIQ1P9BWy37HUqG567ttnT46M+vkxrIj/qgs2tI4VGBL968sqm00OYDSBDCLjWE5vRyhB+6uQV3L4/jxtblJjcd3QKl9dKPfcvbJZNZf2DAKA3ZQhtqz8VVGZ4kfOw00PYeFvQyE2LbiqjV9Ycv61DU72r6t2xfwIvLhV6EqyJM4VCYbdPAesqM4RNxvRxKhkdhrFVSasMocoMcC5lYLPHgPDSagkH+5ivAOCWvc6G13PXetvIivr4Mq2J/Awm4JQZMhGBGkVlSq7xdBAZQgCYG09hMUIZwitrJZy8tI43NWUHJbftc3YOT13t7Ytis1xTZjkBAJrmGNIDboaQd3MigxSQsUXda1JVhlDXyFlkdQnaFtzycCko1QtSWOYUZwmHHqkGq0ZlVPOChaplK+0xY8LFyxBadVGZMEpGu/X4bZRrWC/VcLDPDOFUNon5fKrnDCETTyI/gxGxMEWUIAD+KbNiOYMbhO0EEL0M4aPnVwEA33zDbMv7b5UBYY+L262KqcxyAmgWlWEfwijhN6YXXoZQ3eTci1DD4lYFukaY7qOk8GZ3t70fX684kkr1HmSrQvYQTigICJ2S0Xj2EA7D2KqkZYZQYcCfTRmwBVCudVbVvrzqVDT0myEEgBN783i+x4Aw6uPLtCYGMxixymiEIKeJ0KNsOr0bQU3W8/kUrm+UI6PG9dj5VYwldNyyr3WP1J7xFPaMp/Ds1d6+KJySUYUZwqaS0X4a55nhpt5D6LedUHe88bTh2aS0Y2Gjgtlcsi/7i335NJKGhvPLLM3eCSMAQSghBE5f38RLS4OVsK0VaxhPGUrmEb3BmF7EqmQ0iLEdZojI2Zy0BaqeqIy6dWTObXnpZpNzyQsI+xd9uWXvOF5Y2PI+s52I+vgyrYn8DMY+hNFCI3iLSQBYK5QDyw4CjtBKuWZ37T0aFR67sIq7Dk10XKzcti/fV8loTmFA2Cwqwz2E0aHuQ1i/hlVu1jl9OV1KRjcrmBtP9/W6mkY4Mp0ZOEiJCzvtQ/rymSW89tcexut/84t48/u/jKWt/kv510s1TCjoHwSAhNaYIYyTMX0cesx0d3yrIYnKAOgqLHNp1dmEGjQgrJo2XlruPnZxGF9mO9EPCKHO/JgJn+aS0VLNCqx/EABmck7p2EqhN5GVYaZUtXDqygbuOTzV8XG37svjzMKm98XXDiGEazsRjqiM40PI125U8JeMyoBQpQL0eDrRvWR0s4K58f7Lo47MZHtaWDGDYVo2/uOfPwUA+JnvuAXFqolf/stTfb/OWrGqRFAGAAy9LipTjZmoTBxIuD6TYZWMAr1lCMcSOqaz/avmnvCEZbiPkGlNLGYwXlJGB6JGH8KyKZBJBtdnNpWNTkD45KU1mLbAvUc6B4S37c+jZglPgr8dFdNGzRJKbSc0zVcyKriHMEq0MqZXuVfXSw/hwmYFewYICI/NZnB+ueiJ4zDbSSYHt3r4+OOXcX65iPd85234l6+9Ae986EZ88okrePj5hb5ex+l5VhUQaqh5thPx6iHcydiOCjJDGJbKKNA9ILy4UsSh6bGBNtJunMtB1wjP9dAeEofxZbYT+RmMwFmGKOFkCH0qo6YItGRUikusRiAg/MYFR1Dm5V0yhL0qjcrFdV5lySj5SkZZVCZSUIsMob6LojKWLbBSGDxDWDFtXNuIjgBV0Ay6qKxZNn7r717AnQcm8Lpb5wAA7/xHN+DITAa/+/DZvl6rULECsyRqJtFgOxGvHsI4BAyGrsGyBWqmqzKqMEOY67lktH/LCUnK0HF8NttThjAO48tsJ/IzmC0EG9NHiOYM4WapGugXvizFWOnRl2+Yeez8Go7PZruWlxybzSKd0LoqjUoJf9U9hP4MoWWy11tUqPcQCs9aROXcnDJ0VMz2PajLWxXYAtiT76+HEHCuGQBcNtqBra3BVFg//dRVXFwp4Se/7Sbv85EydLzh9r14/MIayrXe+4qLVROZAFsK/Bi6Iypj2cLZvIpRQDjo2I4SMkNYCUFUpveS0eJA/YOSE3vH8fz17noBcRhfZjuxmMG4hTA6EKEhICxWg+0hlCWjvRq1DytCCDx+YRX3dCkXBZwvvpvnx3H6euedQ/llpaoEC3DGV1bh2bbg7H6EaCwZlaIy6o6XTuiodJBxX9h0REr25AbJEDq79C8tsdJo0Hzu2QXsGU/hH52Ya7j9gePTqFo2HnOtdHphS2WGUCfUfCWFcRKViQOGRrBsGzUzvJLRQqX9Zsd6qYaNsrmjgPD4bBaXV0td9QKYeBKDgJBtJ6IEocmYPuCS0WxSR0InrBRGOzO1uFXBcqGK2/fne3r8/omxruVvsvwurAyhxT2EkSJsH8KUoaHqZnBasegGhP2Y0kv2T4y51hOcIWzHIGVnli3wpRcW8eBNs9uyx/cfnYZGwFfPLff8esWqGeiGoR/DtZ0Io8ds2IhDSeG2HkKlojLO91ynktGdeBBKDk1nYAvgylqp4+PiML7MdqI/gxHYdiJCNNkQOiqjAe4AExGmMsmR7yE8c90p+bhprrX/YDPSf7ETsmRUpQ+h3uBDCCQT7IcUFciXIbRC8CFMJ5x5od1u+MKm83kfJEOoaYTD0xm8yNYTbRnE3Prpy+tYLdbw2pv3bLtvPJ3AnQcm8A89BoS2LVCsWsgoEsGSKqM1t48wTiWjcTAuN9zNSS8DrNJ2Itm9ZHQnlhOSIzNOqfv5lc6VDXEYX2Y7kZ/BhOCysyihNfUQlqoW0gFnkaazSayOeMnomUU3IJzP9fT4uXwam2UTpWr7kpW6qIy6klGtyYeQewijg8wQipBsJ9IJ5+utXc/ZwoZbMjqAqAwAHJ3Jsjl9BwbpQ/rC6UUQAa++cbbl/Q/cMIMnLq51nKckJXfcswGqUPtJuCqjYQQMw0YcesycHtG6D6GhsL5d0wiZpN4xIJRZvf2TgweEh6ed7OKFLgFhHMaX2U70ZzDBGcIoQU3G9LZwSjuCZCoz+gHhC9e3MJ42elZQnHeFNWTWpBXyyyrIEt1mGn0IBTQ2jYkM9R5C4ZV9q1QZTbkbRZU2GcLFrQomxhJeJrFfjs5kcH6lwNYTbfCX9vfKF08v4o79E5hpk7X9puMzqFkC3+ihj7BQdeYrZRlCV2W0blwen7lqkLEdNQyNYNo2qpZAUteUixNmU0bHktGVYg1EzvpkUObGU0gZGi50KXWPw/gy24l+QAi2nYgW1FAyKoQI3GhyKpsYeR/CFxY2ceNcrucvsXm3j+q6mzVpRdkV6BgbcAHdCzJDKBfZ3EMYHbyA0Pb7EO5uhnDQ7CAAHJ3Nolyzcb3DJkqcSST6qyRYL9Xw+MW1luWikvuOTkPXCF97sXvZqBToUJUhNHTNUaE01feYDRv9ju0oovtKRsMI9sdTRscM4VqxiomxxI42wDWNcGg60zVDGIfxZbYT/RmMiFVGI0SzyqgAQAFHhE6GcLRLFc8sFHDTXG/logAwN+5kCDv1EcqFdUrhwkfXnMyg7DHjHsLo0OBDaKtXGe0lQziIB6HkkFt+dWm1s0BDXOm3D+nRl1Zg2QKvvql1uSjgqDEemcngzEL3kraC4oqGhPvhlfNinEpG49BjZvhEZcII9rtmCAvVHWUHJUemM11L3eMwvsx2Ij+DCfYhjBSuk5n3uxDBLyqns0msFasjWwq2WqhiaavSs6AM4M8Qtg8IK6aNpK5BU7iKlyWjXtmo1dmXiRkd5OdGiHqGcFd7CDfLOwoI97pl1tfWOUPYimKxv/7KZ1wf1DsOTHR83OEeMhyAY0kEQJ3KqBsAyuPEKSDsd2xHkcYMYRgBod7RdmKtWMNUZueZO5kh7FQWGofxZbYT/RmMewgjhUYEf5zmBPzBHmMqk4QtgI3yaGYJpaDMjX1kCCfGEkgamufN1opyzUIqoXbKcEpG632ijQXCzCjjt50Iw4dQZghbBYRCiB2XjMqAsJs6b1yx7f68zk5d2cDRmYznydaOI9MZXFjuvKAF/D2E6nwIAcfawv97HOh3bEcRx1bEKQkOIyDMdSkZDSxDOJNBsWphuUNbTBzGl9lO9ANC4h7CKOGUjPoyhFBQMpp1duFGtY9QllP1ExASUVfriYppe4tsVTRnCBM69xBGhZbG9AojQpkhbFUyulkxUTFtr1R6EPJjBtIJjTOEbTCM/jJzp65u4Pb9nbODgJPh2KyYWOtS1l+sKM4Qup9dqXgaJx/Cfsd2FKlnCEVoJaPdeggnAwgIpdJop7LROIwvs51YzGDcQxgdCGgSlQk+Ayx34Ua1j/CF61sYS+g40Kc89fx42pPib0WlZnmLbFXonqiM83sqyc3tUaGhhzAUUZn2GcKVLWezZzo7+AKLiLA3n8Y1zhC2JJ3uPdjeKNdwYaWI2/bnuz62Vy+1eg+hOlEZoF4yGidRmX7GdlQxdEdltOa2SqimWw/harGG6ezOvw+PzDgB4cUO108cxpfZTuRnMKfHjCPCqEBNPoQCwfchyUXiqJrTv7CwiRvmsn1nX+bz6Y6KiU6GMIyS0bqoDPsQRgc5D4vQSkbbZwjlTnwuvbOd8Pl8mktG29BPH9JzVzcBALft6x4Q9uqlJktGVWUIvZLRGIrKxKHHzC8qkzDUryE7lYyWaxZKNSuQDOHBqe4ZwjiML7OdGMxg3IMUJfw+hMLrMwsWmSFcGVEvwheXCrhhT+/lopK5fKpzhtC0BvZs65XmklHeyokOcixtUb92dytDKHfiu/WrdWPvBGcI29FPH9KpK+sA0FOG0AsIu3ipycydqh5CQ3OWTyWvhzAGyymXOPSY6W4PYTUkUZlcykDFtGFa2/+20hc5iB7CdELH3nwa51faXz9xGF9mO7GYwThDGB0I5MX4wlMqDPYYUyOcITQtG1fXyzjk7gL2w3w+ja2K2WGXMqwMYT3o12O0yIo6fmN6ud5QOTd3yhB62aOdBoT5NK5vVNjIuQWa1vu1+8yVDcxkkz2pvo4ldcyNp7pnCCsmDI2UlfsZnqiMLBmNzzqjn7EdVQy3h7AakqiMnItaKY2uFpxKmSBKRgFnU6VTyWgcxpfZTgxGncCf7ehA9XjQ+3/Qi8psUkdS10ayh/DaRhmWLXBwqr/+QaBuPbHQJuNRMa1QRGUAoObukqZTO98RZYYDv6iMLAlWuVeX6pAh3ArItHw+n0bVtEdyrlBNJtP7ptSpqxu4bX++5/L/wz14qRWrFjJJXZm1iQwSSjEsGe1nbEcVXfYQWuo3QgEg52ayt6rbN2RlhjCIklHAqWy43qEaKA7jy2wn8jOYgOAMYYQg1MvNbEUlo0SEqWxiJDOEl12T7AODBISeOX3rL4pyzQ5BVMb5f81yx9hkH8KoQO7YCiFCKRntlCEsBmRavneCvQjbUS739jepmjZeuL7VU7mo5PBM5wwH4PSJ7rQkuBPNKqNxCgh7HdtRxvCpjIaZIdwqtw8IdyKC5UcqirerbIjD+DLbif4MJrgPKUrIkkJAXcko4NTqj2IP4SUZEPapMAo4PYSAY9jdijAyhFIIx+ujENzLEBXqojJ1Y3pdoapMytBA5KjjNrMVUEA4z16EbTF73Mw5v1xA1bJxy97xnl/78HQGVzfKqJjtjbyLVRMZlQFhU8lonALCXsd2lNH9ojIheEx6AWGLlg1ZgTAZgDE94MxbFdPGeql1ZUMcxpfZTuRnMBUqlMzu4dhOuKIykGVnwY/vVCY5mhnCNScg3D9QQOgsbtsJy4SSIXTHsuoGhNxDGB3CNqYnIqQMDeVWPYQBlYx6GUIOCLfRax/SS27p51HXTqIXjsxkIARwcaXU9jGFirXj8e1EXVQmfj6EcegxS2haqD2EOa+HsEVA6K5FJseCyhB2rgaKw/gy24n8qBOIfQijBNUzgyozhNPZpFemMUpcWi1iz3hqIDXQ8ZSBsYTednEbSg+hJnsIncEdS3cXmWBGg0Zjeuc21Zt1KUNvmSEsVE2kDM3zkhuUufEUiLhktBW99iGdd9VCj/QREEql0U5lo8WqiYwiywnAnyF0VUZjJCoThx4zXSfUXJXRMIL9jgFhsYrxlBGY16XcyGpX2RCH8WW2E/mAkHsIowWB6qIyon5b0ExlE1gZ0QzhIIIygNs7mUlgrY1ARsVUnyHUmkRlbItLV6KC35hehJAhBIB0QkO51ipDGEx/WULXMJtLccloCyqV9qIVfi6sFDGeMjDVRzncoR68CAsVS5kpPVAvEY1jyWivYzvKOD2EjqhMUIFYJ3IdSkbXijVMBqQwCtT1Atpu/vY5vsWqiT/80ov4i5NXeC4cYdRtnw0JbEwfLTSqi8rIklEVi8qJsQQ2yiaEECNVcnxptYQ7D0wM/Pxsymi5Qwk4ao0p1T6EMkPolvkJ9kOKDH5jeukzqXpuThl6yz6zQsXccf+gZG+evQhbUav1prx6frmIwzOZvubZmayTmV3usGlXqAY3xq3wRGXcDLQRo1KkXsd2lJE9hBSyqEyr79+VQjUQD0LJXBdF8X7Gt1S18KMffBRfPbcMAEjohA/9yCvwqhtnd36iTKjEY0srPvN05CFfyaitsGQ0l0rAskXL7MKwYtsCV9ZKODiAB6EklzY8jzY/QghUzHB8CAFfD2GMFllRp1XJqOqAsF2GcKtiBRYszOfTXDLagl4DvAsrRRyZ6W/O0jVCPp3AWoey/kLFUloy6s8QJnVtpDYOd0oc3mv4PoSu7UTLDGGwAWE6oWMyk2i7kdXr+Nq2wDv++FF87cVl/Po/vQufetercWg6g3d/7ORIajDEnaEKCInoYSIqE9GW++/5pvu/n4jOE1GBiD5BRNPdX1N9WRITHo0lo8K7LWjG085CYrMyOjuhC5sV1CwxkOWEJJcyWn4hVS0bQmCg3sR+qPsQOmObzQz+XpjhoqWojOJvoI4ZwoAER/ZOcMloK3K5XNfHWLbApdUiDk/33j8omcokOvo/FqvBjXErZA9hqWqFokI5TPQytqOOrmkwbaeHMIz+0JShI6GT55HqZ7VY66ukuhfmx9t7EfY6vl84vYi/f2EJv/Bdt+Mt9x7EnQcn8P++9eVYLlTwHz7+VJCny4TAUAWELu8SQuTcfyfkjUR0O4DfA/ADAOYBFAH8TrcX45LRaEENJaP124JGBoStPIGGlctrTj/NoD2EAJBNti4ZlV5uqjOEdR9Ct4eQ5a8jA/kyhGH4EALtM4TFAMsJ9+bTWC3WUG4hXhNneulDurJWQs0SfWcIAceku12G0LaFY0yvtGRUZghNJELoMRsm4tJDaFquMX1I/aHtWjZWC9XATOkl8xPptiWjvY7vh//hPPaMp/DW+w97t91xYAL/5nU34zPPXMPTl9cDOVcmHEZpFnsbgE8JIb4ohNgC8B4A30tEHc2LWFQmWhD5fAjt+m1BIxu8N0coIJQehAcHsJyQOF9I2xe2crGruoeQRWWijewBDq9kVEe5RYYwSNPymZzTjzOKqsQqqVa7/z2kKMyR6f4DQidD2PoYsq9PZYZQZgULVStWgjJAb2M76hg6uZtX4QkGZZPbWzZqlo3NihmYKb1kfjzVtmS0l/G9uFLE3z2/gO+7/9A20Z23P3AEKUPDnzxyIZBzZcJhGGex/0xES0T0ZSJ6yHf77QBOyl+EEGcBVAHc3O0FOR6MDv6h9HwIFRynk+LXsOKZ0u+oZFRv+Z4rtbAyhG4PoZuR1LjeO1JoRKH5EALO57XSUmU0OAVKWco1iqrEu81514Pw8AAZwqlMsq0issyyKBWVcYOEqhmOLQETLn6RoLAywKmE5lXjSOSmR9Alo3sn0ljcrHgCX/3yka9fgEaE73vl4W33TYwl8I/v3IdPPn7Fs2Vhhp9hUxn99wBOwQn03grgU0R0txv85QA055/XAWzLEBLROwC8AwAye49D2DY2Nja8XY9sNgvTNL20eDabhW3bKJWcBbX0YCkWnS+rsbExaJqGQsHxS0qlUjAMw/s9mUwimUxia2vL+z2VSmFrawtCCCQSCaRSKRSLRdi2DcMwkE6nvd81TUMmk0G5XIZpmt7vlUoFtVoNRIRcLodKpeK9h1wuh2q1Grv3ZLrqV4uLi6hR0n1PBSwtLQX6nsyy85iVzSJWVlZGYpzOXF3F1JgBXVhYXl4fbJyEiULFxNraGkzT9N7TytoGAKBWLqJcLit7T8WC83cvlp3Xtk0TGxsbQ/HZi+L1FPZ7IgKKxRI2NCeDU61WsLam7j0ZBJSqJpaWlhre02a5Bs2uYXNzc8fvKet+i56/uoR9aSsS4xTEZw+A93dv956eu7QEQyNMJASKxWJf72k8pWG1UMHS0tK293Rt01mEiloZS0tLSq4n064vnzQ44zOK4zTIZ69arQb+nbvb76l5nMru/QAA2/I+yyrfkwGBzUIZlUrFe08vLjnnlSKr6/XUz2dvKq3BFsALF65i/3Su4T0JIVCpVNq+J13X8aePXMSDxyeRqBWwslLa9p6+5655fPzxy/jYV17Am+6ci828N+zvqROhBYRE9DCA17a5+8tCiFcLIb7mu+1DRPR9AN4I4LcAbAHINz0vD2Cz+cWEEB8A8AEAmDx8QhiGjny++anA+HhjLJnNNja2N5tzjo2Ndfw9nU43/J5KpTre3+/v3V4PiP57SiadIHBmZhZrJSc4HM/lMDtblzgO4j0dEs5jKraG6enpbfcH+Z6AYMZppXwOB6ezSKVSA4/T7MQaTFsgnR1vEJDRU87xZqcmkE6nlb2nibybZdF09zUy3rW7258953yidT0B4b4njQjJdBqZrPMaY+k0JnOdz3kn7ymTvoSqJRrmByEESjULsxPj3vN28p7mK85n1TLGvLli1MdpkN+bX69arW773m1+T4slgcPTGYzn3PHq4z3Njo+hULWRn5z2StbkOVyrOHvHc9MTDWMf5PWk+TLC6WTCO7dRG6dBPnumaTaMbRTeU/M4TYzXhVWyY6mGz9Eg59DL79mxJISmN3yHn91w7BwOzE5sO4edzBEHZ5wgo2rUv2PlOclN2Hbv6YXrm1gqVPHGu29pe329ekrg2GwWf/XcKn74oVsBxGPeG4X31I7Q6hyEEA8JIajNv1e3exrqFYHPALhL3kFExwGkAJzufFwWlYkS1EKpUK2ozGipjM7nU90f2IFcGy+k8ERluIcwymhEEALetavaViSd2K4yWq7ZsEVw5YRSDr6TBUIc6aUPSXoQDsKk21O1Vtp+HGkWn1VoO2H4lEW5hzB6+OemZEgqsmlD3yZOteHqGOTTwZeMAmipNNptfL/24goA4IFjM20fQ0R489378ej5VbagGBGGZhYjokkiegMRpYnIIKK3AXgNgM+4D/kfAN5ERA8SURbALwH4uBBiW4awGW5Dig5yLAXqfoQqhjc7gj2Ei5sV7BnfWUBYN8dt/FKquF9Sqm0n5OaN9CHkazdaaOQoQNY9RFUb02/vIZTXdC6gHsJJr4dwdDaPhgEhhONBOICgDFDvqWrVRyiFOYLqE21Fwld+1SyqwYw+uxHwp1qoIssevLGABZLm8zIg7N8y52svrmBvPo1D0531Ch68aQ+EgGdazww3wzSLJQD8CoBFAEsAfgLAdwshTgOAEOIZAP8STmC4AKd38J29vHAcTFTjghxLIXyiMgrGN2loSBnayKiMWrbASqGCPbmdZgidL51m/8XQM4Sm9CEcbLHIDCcaUZPthNrjtVIZldnvoEzLE7qG8bTBKqNNNJdFNbNRNrFVMQcWwZocczKErbIP4YjK+DNIw7SUUk+3sY0C/gxhWAFhuoVvasnNdmcCDghncylo1Dog7DS+Qgh8/cVlvOLYdNe1110HJ5BLGfjSmaUdny+jnqERlRFCLAK4v8tjPgLgI329LtRkkJjdRUDUM4SKBng8bWBzRDKEK4UqbAFlGcJySBlC+b1r2k4AKmz2dosSRE3G9KptJwwdNUvAsoW3wKtnj4L7+pvKJDkgbMLs4iEqPdBkpqJfZGa2lTl9saJmEe2nUYUyXquMbmMbBfwZ4NACwhYZwoKi8mddI+wZT7UMCDuN74WVIq5vVPCKY9NtHyMxdA0PHJ/BlzkgHAlisa3FPYTRQQ6lEP6SUTXjm0sZI2NMv7jp9AEEFxDuTg9hc8moZXIZXpTQNIIQAu7wKp+bUwnn8+rfdZebHUH5EALAVDbZMjCJM93MrRfcOWvQgHAq27530wv6FfYQEpEXFMathzAOxvT+DKHq7736cbb3EJYUlYwCwEw21dIup9P4ev2Dx7sHhADw6htncH65iIuu5ygzvER/FhNAF6VVZoTQWpSMqio7y6WNkekhXNwKJiBs578oF9TqM4SNJaM6b+ZEClkyqlIQyk/aXcj5d93r5YTBfZanMgkWTuiT6zvMEE51yhDKMjuFPYRAvWw0bgFhHNiNHsJ0Cx/CYtWCoZGSPtXpbLJv/9SvnVvBdDaJG/bkuj8YwKtvclRIOUs4/ER/FiPuIYwSciQF/MIUao41nkqMXoYwN9jiStIuQ1gOy5ieGlVGs1nuIYwSmlsyKkJSGU25Gxj+DOGWgv6yaS4Z3Ua3PjOpbjg34CbWWEJH0tBaZwgrJhI6IWWoDQhlWSH3EEaPxh7CkFRGE9szhMWqpSQ7CLSvbOg0vicvreGew1M9r6tv2JPDfD6Fv+eAcOiJ/CzGthPRorFk1M0yqCoZTRvYGBHbCRkQzo4nd/Q6uWTnDGFKtcpok+0EybpgJhKQlyF0flfeQ5jYniEsKughnMwkOUPYhG3bHe+/vlFGLmUMPA5E5GRm2wSEY4rnKsCfIYzXGqPb2EaBxh7RsEpGnQyh8H3vlaqWsl7Y6UyiZYaw3fjWLBsvLRVwYm9v2UHAuU5fcWwGT1xYG/Q0mZCIfEAIsKhMlJDBn5NlcG9TliEcoZLRzQpyKWPHyomyjG67qIzzBZEOSWVU9hDWqtHvVYkTGjkbOXZIKqMyQ9SYIXR7CAPsL5vOJlCoWtsUAuNMqVTqeP/CZhlzO/RNdcR8tm/alWu2sqyKH8PNDMatZLTb2EYB3W8rEprthJyvfBtYNUtZL+xUNon1Ug2m1RgAthvf88tFmLbouVxUcueBPC6vlfouT2XCJfKzmIBgL7MI4WUI4ROVURQRjloP4U77BwFngZNOaJ4og6RiWtA18hZAqtC8ktFwAgYmXJwewvB8CFtlCD3biQD7yyY9c/rRqCgYBhY2Kpgf31mJ+2Qm0bJktGbZoQRpCSkqwz6EkcOfIQzLZ1L26Pu9U4sVU9nmxrQUZir1Nm+dWdgCANw4119AeMf+CQDA05fX+3oeEy4xmMWIS0YjREsfQkXHkiqjYgTKFhc3yzv2IJTkWmRGyzVbeXYQ8IvKcA9hFPFEZexwNurSMkNY86uMmkgaWqABw5QbEHIfYZ1MFw/R65tlzCvKEFYsO5RFvO6Wisath7Db2EaB3RKVAdDgnVpUWTLqBoTNmbt243t20QkI+80Q3n7ADQivcEA4zMRiFmNRmejgjaTfdkKhyqhpi22qX8PI4mYwGULA6a3abjthKe8fBLaLyrDKaLTw+xCGsVGX8hZYvgxh1QzUcgIAprKO4iWXRPWGEALXNyoDK4xKJjPJ1hlC0w4lSJOiMnHrIYwDuyEq45W41xpLRscUlYxOZ1oHhO04u7CFfRPpvvt+J8YSODydwTOXN/o+RyY8Ih8QCsElo1FCriFtIfOD6oQpxtPOIm9zBJRGAw0Iky0CwpAyhLJtQ/YQVirR71WJExoRhCsqE8a8LBdY5VqjD2GQlhNAPUM4aMno184t4z2feBo//8mn8dWzy0Ge2q5RLLb3HVsv1VA1bcztMCCcyiSwVqxtq+KohpQhjKvtRKexjQrGLvQQtsoQlqomMoo2Y6WXZ7MgVrvxPbO41Xe5qOSOA3k8xSWjQ00sZjFOMkQHz4cQ6r3Mxt1dsM0hVxot1yxslM3AAsKWJaOmHU6GUOMMYZTx206EUbmR9ozp6zvuWxUzcJGGdqVXvVAxLbz7YyfxsUcv4qOPXsQ7/uhRTzU4qkjLiSBKRk1bYLNpvqqGlCE0vAxhLJZSsULfjR7CFhtYoZSM9lDqLoTA2YWtvstFJXccmMCFlSLWuc96aInFLMY9hNGhbjtRVxlVRTuT9mFjSZrSB9RDmE3p21RGKzVLuQch4C8ZdQY3kxlTfkwmPPzG9LuXITQDtZwAHHETAC3LF7vxsUcu4vJaCb//g/fhr/7VgyjVLPz63zwf6PntBmNj7a/dhU3HlH4uAFEZAFgrNC4yQxOVkT2EMROV6TS2UaHBdiI0ldHtG1jFqhWoAJYfef00Zwhbje+1jTIKVWvwDKErLPPMVc4SDiuxmMW4hzA61I3p6/9VFfDn0m5AOOQlo54pvcIewrAyhM0+hAld/TGZ8Kj3EIazUddqgVWoWoEHhClDRzapY6XQ3+53uWbhtz9/BvcdmcKDN83ihj05/NCrjuKjj14ceUU+TWu/vAgyQwhsF/OpmmGVjMazh7DT2EYFfRcCQqky2pghNHdsJ9WOlKEjlzK2zVutxlcqjO4kQwiA+wiHmMhf1QIsXR8pqO5DaKsWlZElo0OeIQw6IGxVMhp2hrDqLuBLpej3qsQJp4dQwLJFKKX8dRn3xgxhTsGOezuBk0782WOXcH2jgne//mZv4/JffetNmBhL4ANfPBf4OYZJoVBoe9/1jWAyhFLMZ1tAaIlwAkItnj2EncY2KjSqjIaziKyXjDrff7YtHE9NhZuxU9nEtuun1fgOajkhmc4msX8ijWdYaXRoif4sFtJONBMOmi9F6KmMKjKeGB+VDOFW8BnCbQGhaXuLa5Vs7yFUfkgmRDQi2HZ4Yl+e7YTZ6EOowuh5OpvsqRfHz9+fXsLh6QxedcOsd9vEWAKvu3UeDz+/sM0wOiosbJSRTxs79leTmd5itbHEvWpa4aiMxtSYPg7IYD+pa6FVmdUrGpzPc8ndyFLVQwg4SqPLPfQ+n1nYwsRYArO55MDHumEuh7OL0d9MGFViMYtxPBgdZPAnUPchVLWwHJUewsXNCojqDeI7JZsyUKxasO16k2Y5pAyhLBk13WOPpXeWQWCGC3/JqB5C2VlCJxA1lmBtKeghBJx+nFaeeO0QQuAbF1Zx75Gpbfd9yy1z2CibeOzCWoBnGC6pVPsNqiAsJ4DWIhxA+CqjcfMh7DS2UcHYBUuR5gyh3OhQGhBmk9t6CFuN78XVEo7MZHYUHN+wJ4dzi1sj4e0cR2Ixi3GGMDrURWUA2268LWhkD+Gwq4wubVUwlUkGtksty+kK1XogXA0rQyhFZdyMTlJR7wSzO4QtKkNESBt6KKp9rRZWnbi0WsLiZgX3tAgIH7xpFoZG+N/PXQ/yFEPFMNpfuwub5WACwkTjAlpSM0UoC3kZNMRNVKbT2EYFWa2SCHFsPdsJd74quQGhKh9CwLGeaFZHbjW+19ZL2Dexs2v2+J4sClULCxFXUR5VIj+LCXCGMErIoXR8CEXTrcGSMnQkDW3oewhXizVPLSwIZPbErzQaXobQ+X/VVRktx8DvKk5ompMZs0PcIE4lNK9k1Lad/kUVC/jJsURfPYSPXVgFANxzeHLbfePpBF5xbBqff24hqNMLnU59ZgsB+aY2L6AlYWUIEzH1IYxTD2GYY5tqKnGXm7JZxSWjvfQQXl0vY9/EztRlj886/YdnF7d29DqMGmIwiwnOEEYIL0OIeg+hykzDeMoY+h7C9WINk2PBBYStSmUrph2y7YQNIlYIjhpOhlCE1kMIoCFDKEuRDQUHz6YMFKpWz+VQj51fRTap48T8eMv7v+WWOZy+voWLK9HbFFktVD2F0J3gZQjNxoCwZoZjOxFXldE4oGvhlwOnmjY4il6GUKWoTBLFqrVtU8VPoWJis2xibwAZQgA4x32EQ0kMAkJildEIIQMEvw+hyqAhl94usDJsrJdqmAxgcSWRght+64lyzQpdVEYnQjIZ3Ptidh9yS0YtO7yNuoYMoTtpaIoCQssWDQI2nfjGhVXcdWjSCyqa+ZZb5gAAD59eDOwcw6TdtVs1bRSqFqYCqGqQm1TNJaOVsDKEu1BWOAzEYV7ejXJg+XmuNJWMqrKdAOraA/4sYfP4XnNVgXdaMro3n0Y6oXFAOKTEYBYTnGWIEJ7IqKiLyqgc3dwIZAjXStVAM4T1ktHwM4R+H0JN44Awamghi8oAjRlCS2WG0N3Fb/bwbEWxauLZq5stBWUkx2azmM0lcfLiWlCnGCrtrt21krPwnAxABIuIkDK0BlsRIQSqpo1UKBnCeIrKxGFe9noIQ8z+ep9nU4rKOHOJSlEZman39xFuCwjXnYBw7w77fjWNcGw2h3NLXDI6jER+FhOCewijhD+4F4p9CAEnINwc9oCwWMNEgD2EzSWjpmXDtEW4ojKWgE6ErS3+4ogSjg+hs2gnhNNImPZlCGXJqIrsZKve23acvLgOyxYtBWUkRITb90+MrEF9u2t33VViDWoTK51oFA2SYxxuyWjkl1INxGFe3i2PSf/nWdpOqCwZlRlCf0DYPL5XZUC4wwwh4JSNcoZwOInFLMY9hNGhUVTGQeX4jqcTQy0qY1o2NssmJscCLBltUhmVi+lQegh9mRuda70jRz1DGI4xPeAINcgFlrRSUfHZ6sem5rlrGwCAO/ZPdHzcnQcm8MLCVsf+nlFDWnME0UMIOAG/v2S0KhWKwywZ5R7CyLEbojJA4+dZbi6p8E2VTGedjZlmpVE/19ZLABCIMvANs1lcWi16XovM8BCTgHC3z4AJClllJkS9H0hlzehYUh/qxdiGm70MUmVU2m1suV9GMiAMI0PoD+41ikdpUpwgV1QmzJLRpKF5QYIl1IrKAI12Le24tFpCOqF1NXm+40Aeli3w/LXNQM4xTNpdu7JXKag5K53QG0RlapYz1pwhVEcc5uXdshRJGboXLMmSUbUZQkftd7VDyejV9TKms8lA1gDH9+RgC+DCcvTEskadyJvJCHCGMEo0GNOrjwe39acMG1LmfiLIHkJ3N7LoZjpkQLwbGcI4GCDHCSdD6PoQhrRTp2sE18XE6yFUJSoD9JYhvLxawsGp7ibPt7sZxKcur+OuQ5M7PscwaXfteiWjQQWETT6TYWYIvR7CmInKxGFellNE2P2h/gxhKQRj+omxBIiAlWLdb7l5fK+tl3fcPyiRSqNnFwu4qY3Ccr988onL+M2/PY2aJXBi7zje99a7kU8HtyaKC7GYxTgcjA51Y3oBQF0/kCSd0FDuUTVwN1grOZN4kD2EcpEje3G8ktFECKIyvqHUNe4hjBpOD6FTMooe7Rl2iq4RLNvNEMqSUQVzRq6FGFM7Lq0VcXCqu6fXwakxTIwl8MyV0esjbHftygyhspJRK8yS0XhmCOMwLxMRDI1CLwf2Z7yLNQsJnZR+vnSNkEsZ2CjVA8JWPYQ7VRiVHJt1rScCEpZ5+PkFvPtjJ5FNGbj/6BS+eHoRP/bBR71gmumdWMxirDIaPZwsg/OzyuFNGcNdMhq0QANQXyzLxbN8/2lDfckoUd0mRgYPTHTQXNsJ2w5vo84JCJ2fLYU9hF7vbS8B4Wqpp4CQiHDHgTyevryx4/MLm3bX7mqxhoROgWU9Uok2GcIQVUbj1kMYl3lZ19QGY61IGVpdVKZqYSyEVo18OoGNcj0gbB7faxvlQARlAEeXYTqbxMWV0o5f68zCFt75Px7Diflx/Mk7HsD73vpy/OY/uxuPnF/BT/2vkwGcbbyIRUDIJaPRoT6WPh9ChUtLv0LhMOJJuAfoQygXy7uRIfQfX9cIiQSXfUQJ8onKGCEtonVqkSFUKirTeQNpq2JirVjDgclMT697x/4JPH9t0wt0RoV21+56qYrJTDKwjVono7JLGUI3WIib7URc5mVDo9DLgdMJ3fvOLVRMpR6EkvxYAhul+kaWf3zLNQsrhWpgGUIAODA5hstrOw8If/+L52ALgf/+I/dj3C0RfdNd+/ET33IT/urJqzh1ZfQ20naTWMxiLCoTHeolo/VdLJXjmzZ0WLbwhAqGjTUFGUKZpZOKjJUQM4RAPejXiHsIo4Y0pg9TVEbXyQsEpaiMioBQLty6ZQgvrzoLoV4yhABwx4EJVC0bLyyMlrBMu2t3tVALdL5KN/V518wQbSd2yZpgt4nLvKxrFHqw71QluT6ENQuZlPrv3YmxxpJR//gubFQABKMwKjkwOYbLqzsTlVktVPGJJy7je15+cNu5/eg3H0M2qeN3v3B2R8eIG7GYxThBGB38ojKyZFRl7ZnMig1rllAGhPkAF1iAFOJwS0Z3KUOoaUCxyEpkUUIjAEJAuP/CwMkQugGhwgxh0tCQ1LWuKqOX3IVQrwHhrfvyAIDnro5WQNju2l0rVQPrHwS2+xBWLefnMDI7dx6YwH1Hpjxl5rgQl3k5oWvhl4wm6hscpaqlVFBG0lwy6h/fq67lxL6J3uarXjgw5WQId/Id8CePXETFtPFDrzqy7b6JTAJv/6Yj+Ksnr+ClJfY87JWYBIQcEUYFOZSOD6EzmagtGXUm42HtI1wv1ZBPG4EvcHWNvAxhvScnnAyh7GHUiWDbwxmIM4Ph9RAKEdqXj6GRV/6sUlQGcPoIu2UIL3kZwt5KRg9PZ6AR8NLyaC1s2l27a8VaoCJY230InTEOI7Pzqhtn8b9+/FWxyxDGZV5+6MQc7j82Heox00a9ZLRYNZFJhFUyWg8I/eN7bSM4U3rJgckxlGt2R+/DTpiWjQ//w3k8cHwat+zNt3zMj776GAxdw//3pXM7OdVYEYtZjHsIo4PmKxmVzvQqS0al1UIvGcJyzcLTl8NVA1wrVgPtH5To5F9EO+89LKN4zcsQEgwjXjvvUUca01tCjfVDy2P6NjdU2k4AjvVEoUsP4eW1ElJGdw9CSdLQcHAqgxdHbKe73bW7WqxiKtCAsNGHsN5DyN/7qojLvPzr/8dd+Cf3Hgz1mM4Gh09UJoQM4cRYAuu+gNA/vlfXFQSEbnXElbXyQM9/5KVVXF4r4e0PbM8OSubG03j9bfP466euefM+05mYBIS7fQZMcLglow0qo8ORIXzf517Ad/7Wl/BLnzoFM6Sew7VSLVBTeomm+cvsnNtCEwHR6hnCdDq4LyFm95E9hEII6CFlVVplCFUY0wOOsEw3H8JLq0UcmBrra946OpsduQxhu2t3rVhTWzIackVDHOF5WR1+ZfNiiCWjharlrVv843t9o4xsUvdEs4LgwKQTEF5eG6z0+EtnFqFrhNfcvKfj495w+14sF6p47MLqQMeJGzEJCDkijAqeqAx8JaNhZAhrnQM8yxb4xOOXMZ1N4g+//CLe9ZHH1Z2Uj7ViLVBTeomukeMVB8B0M4RhXUfyOLpGselViQsawfMhpBB9COVnWfbFqs0Qdi8Z7bVcVHJsJoOXloojJfff6totVS1UTDvYklHDKRmVfxspAJbgDKEyeF5Wh1/ZvBhShjA/5gR7m2Vn7vKP72qhiplcsCJCsn9als/3y5fOLOPuQ5NdzecfOrEHSV3DZ5++NtBx4kYsAkKOB6ODZzrh87VWObwpmSE0O2cIv/biMq5tlPGL33U73vGa4/jMM9cGro/vh42SmoDQn1WxFSoztkImjjTuIYwcTg+hcHwIQ5qXdf9nWXGGsPeAsD+BhqOzWWxVTCxtqZ9TgqLVtRu0KT1Qn6PlIjpMH8K4wvOyOtIJHaYtYFo2ilUT2TBsJ9zASgrL+Md3uVDFVDbYtpSJsQSySX0g64n1Yg1PXVrDN9842/Wx4+kEXnXjDD576tpIbabtFrGYMVlUJjrIsRTCayFUOr69Zgg/+fgVZJM6XnfrPF5/2zwA4OsvLis7L4myklGq912ZltpFdDO6L0OohWRNwIRDg6hMSPOy7it/NhWLyuRSeseS0WLVxEqhOlBACIyWsEyra1eFTY4s65dztOwhjJvQS5jwvKwOueYom3ZoJaNyU1n2EfrHd6VQxUzAASERYf/kmGfB0w9fObsEWwAP3tQ9IAScstGLKyU8d220VJp3g1hc1dxDGB00X8mozFypXFeme8gQlmsWPv30Vbzhjr0YS+p42cFJjCV0fPWs2oDQtoUjKjOmQFTGt4i2FZfZNeMXlclk+iutY4YbaUwvBGCEqFprNWUIlZWMJjuLysgFkOyh6ZVjM05AOErCMq2u3TU3QxikEFY6IRfQzt9dZghTIRuKxwmel9Uh1xzFqomKaYdUMupmCF1zev/4rhaqmA44IATq1hP98qUzS8gmddx9aLKnx7/u1nkQAX976nrfx4obsZgxuYcwOviN6RFGyWgPGcKvnl3GZtnEm+8+AMBRBbzv6BS+ek5tQLhVNWELKMkQ6q1EZUIrGZWiMkC5PJgKGTOcaEQQwu3lE+GUnbUypldaMtrBh/C6a/Lcr6fXwakxGBrh/AhlCFtdu2tuBiLIOSttNAp/1TyV0Vgsb3YFnpfVITc4ZDY9FFEZt4dQlozK8RVCYFlVQDg5eED4wPGZnisA9oyncMvePL7+4krfx4obsZgxOUMYHaTnoN+HUGXA75UjdcgQnl3cAgDcfXDSu+2B4zM4fX0LS1sVZee27n5hqBKVkYtnK2RRGX/JqGl27sdiRgtpO2H7d3QU488QmoozhDm3h7Bdv8paSWbI+rtmDV3DoWlHWGZUaHXtqughrCtBN/YQcsmoOnheVkfK3eCQGgRjIfYQypJROb5FVwRKVYZwrVjr2nPtZ2GjjPPLRXzTDTN9Heu+I1N4/MJqaOrvo0o8ZkzOEEYHr2QUkH3PYZSMdsoQXlotYTxleLtsALwJ62vn1O1Kef04inwIrZCk+pvxSkaJewijhicqIwA9pLE1fJsbtuIewkxKhy3QYJTuZyc9dEdnRsuLsGMPYcDG9EA9Q+iJynCGUBk8L6tDfp5lQJhJhNdDuNHUQyjPYVrBGqNuPdF7lvCZqxsAgDsPTPR1rPuOTqFQtbiPsAuxuKo5QxgdtFaiMgqLRusN3u0zhJdWS9t8xe48MIFsUsdXzy0pO7dBsw290Gg7EW4PoT9DyL0q0YKIYNtOKVLCCKeHUNOcMlXbFt7mhirFXOnV1U5YRu7A5wcJCF0vwlFRy2vXQ5hOaN5GWxA0e8XKktGwNrDiCM/L6pCquU9dXgcAHJ1V/7fOJHXoGnklo3J8vYBQQYZQCmv1ExA+6waEt+7P93Ws+49OAwAefYnLRjsRk4CQvxiiQn0khbcwCkVUpoMx/aXV4jbVwISu4eWHp/DExTVl57amuGRUqovaivuumpGBp64RKhV1JbdM+Ph9CEVIPYTyc2sJ9QGhlIhvVwa1XqphLKEPFBAdm82iWLWwuDka10Sra3c1YFN6wC8q43yeKpaNpKGxurhCeF5Wh+yJ/crZZSR1Dbfv7y8bNghEhHza8ERl5Ph6AWEu+IBwv5shvNJHQHjqygYOTY919R9sdaz9E2k8cp4N6jsRk4Bwt8+ACQr5He9I1zfepoJuojJCCFxuYzR9fE8W55fVmUl7Ag0KAkJZ2gf4pPp3wYewVquFckwmHDzbCRt1I1HVx5QBoS280lFlAWGXDOFasTrwBs7haWeOubAyGn2Era7dnbz/dqSaRWVMgRT3DyqF52V1pNwNjqcureH2A/lAs+mdyI8lvAoGOb4qS0b35FIgqgtt9cKpqxu4bV9/2UHJfUen8ehLKyNTYbEbxGLW5J3C6CDLQ51rWjTcpoKErkHXqG3J6EbJxGbFbOkrdng6g82y6WXygmZjB+Vn3WiwnZAlo7sgKsPXbrTQtLqoTFifJ8MfEIZUMtouQ7hWHNw3VO6oX13fXYVHIURP4gytrt2Nkhl4QNhcxVG1LCS4f1ApPC+rQ2YIbQHcc3gqtONOjCW8klE5viozhIauYTaXwsJGb/NZsWrixaUCbts3WMb0/qNTuL5RwaUBvA/jQixmTZ66ooPnQ+h6mQHOIlMlKUNrmyG8uOrs1rcKCI+43mHnFe3oF6smdI2U+G3pGnmZwbBtJ+qiMkAulwvlmEw4kM+YPplQr54H1DcyTH9AqGhBm005i7l21hPrpdrAAdG+iTQA4Or67i5o/s1Hn8BtP/9ZfM/vfBmff26h7eNaXbuFqukFzUEhS0YrPpXRJGcIlcLzsjrk5xkINyDMpxPeJrMc3+VCFQmdMB7wNSvZm0/jeo8B4XPXNiEEcFuf/YOSe484fYTf4LLRtsRi1uQewgjhVxn1fAjVjm86obfNEMqG6AOT20tGj8w4t6nyDitULGSSupLdWr+ojGc7EbKojEbcQxg16j2ECK1kVG5khCsq03q+2ElAOJ5OIJcycGVt9zKEp69v4pNPXME9hyexsFHBez75dNsSrFbXbqFiIhN4QOhmCE0pKiOQMPg7XyU8L6sj5SsRvefIZGjHzY8ZXslovYewgqlMUllGeD6f6rlk9NQVR1Bm0IDw5vkckoaGZ66sD/T8OBCPgDAW7zIetPIhVB3vd8oQyvKDdiWjAHB+WU2GsFAJfrdd0mA7IUSoin1+UZlqtRracRn11G0nwhOVkcGfGUJAKHsIiwpKRgEnS3htF0tGf+fzZ5BJ6vjdt92Ld3/bzbi0WsJjF9ZaPrbVtVuoWsilgu2J2lYyyhlC5fC8rI60W/GzfyKNfRPb1xWqcEpGnXlLju9KoaZEYVQy10eG8NTVDUyMJbDfrZToF0PXcGJ+HM9eZeuJdsRi1uQMYXTwhlLUEwyqR9fJELYLCIvIJvWWi7x0Qsd8PqUsICxWnQyhCnSNPJ9H0xahZQcBX4aQ1aAihxSVESLEnlR3R9AWQyAqU6ruyDd03+TYrpWMvrRUwF+cvIK3P3AEU9kkXn/7PFKGhk+dvNLzaxQrJjIBG23LBbRnTG/ZSIZkacIwQSM3OF5+JLxyUaCxZFSyUqhgRkH/oGR+PI3lQtXzDu3EqSuOoMxOspW37hvHc9c2Bn5+1IlFQMgN0NHB8yGEz4dQ8fg6GcLWJWCXXIXRdudwZCaLCytqSka3VGYINYLpRoS2HW6GUC7WdSLuVYkYRHVRmWQieDGkVshkkWmLujG9MtsJt4ewRclouWahXLN3JKqyL5/eNVGZj3z9AgxNw4+9+hgAp4T1W26Zw18+eaWlyEzztWvbAoWq5f2NgsLQNRgaNWUI+TtfJTwvq2MsoeOugxP4x3fuC/W4+bEEKqaNcs3yxnelUA3cJsbPfD4FAFjc6lw2KoTA6eubOLF3fEfHu2VvHktbVSxs7q4w17ASj4Bwt0+ACQwZdwmBUHwIAaemv32G0DGlb8eR6YzCDGHwu+0STSO4NoQwbaFMhKPdsQEuGY0iGjkm8ZYdZsmomyG0Rd1CRdHn2dA1pAytpaiM3H3fUUA4mcbiVqWnHfWg+dq5Zbz88CTm8vWSrTffvR9LW1V89dzytsc3X7slN2DLKtjESif0eobQdHwIGXXwvKwOTSN88l2vxhvDDgjTznW5Ua75SkarmFFYMjrvziXdykYXNysoVi0c35Pd0fFudS0ruGy0NbGYNblkNDrIkbR9KqOqR7dThvByC1N6P0dmMljYrKDYRnVwJ2xVLCWLK8AR4rB9thPhlow6/9eIA8KooZHv2g0tIHT+7+8hVPl5zqWMliWjnm/oDnsIhei+gAqaYtXE01c2cP/R6YbbHzoxh7GEjv/97Ha10eZrVwbJQYvKAI4yY11UxkaCewiVwvNy9JD2VRslE9VqFTXLxkbZxFQIAWE364mX3E11qdw+KNLD8LmrXDbailjMmtyKFB28DCHgicqoDvjb9RCul2rYKLf2IJQcdicwFWbSxarpydwHjUZ12wlzt0pGYzE7xQu/qEzYPYSWLTzlXJWf52zKaOlDKBX8Jsd20EPoikxcCzkgfOLCGixb4L6jjX1N6YSOm+ZzOLu41fU1ZBlt0KIygGNOX/ch5Awhw/SLFxC6XoSrrgeh2gyhUzLaTWn0pSWn7ebozHY1936YyDiiNM9yQNiSWMya3EMYHeRYCiE80RPVw5tukyG80sFyQnJEodJoQYFAg0TX6ob0tgg3QygDBV0jZLM72xFkhovd8CGU5aGWv2R0FwLCtWIAJaOuwp6ce8LikZdWQQTc00Lo4oY9OZxd2B4QNl+78m+iYs5KJzT2IQwRnpejRz4tM4Q1ZLNZrBRdU/psStkxpzJJJHTqusH10nIBhkY4MLlz1dVb9uWVlIxuVUx85ulrePry6NpahPONvMtwhjA6+ERG66IyiotGUwkdlTYZQgCY6lACJr0ILygJCIOXcJfoGnmKjNYuZQg1Iphm8KW2zO7R4EPoXcFqqdtO2N4mh8rsZC6lty4ZdRdYOyoZdRdEYVtPPHp+BbfszXuLRj837Mnizx+/jELFbChhb752i1W3h1BJQNiYIUxwhlApPC9Hj4kx57pcL9VgmiZWtpz5aiqrTvxL0whz492tJ84vF3FoOgMjgI2eW/eN44unF1ExLaQCUiP+zb89jd/9wllUTRtEwA9901H89LefULZhr4pYzJqcIYwO/gxhWKIy7TKEW65nTy7d/qKfzCQxMZbA+YCVRi1boFSzFGYINa/fyrTDK+8DGkVl2AA5WtRtJwSEHU4PYd2YHpBimCo3ODJJA6Xq9vlCbiBN7CAgzKUMjKeMUJVGTcvGY+dXcf/R7dlBwMkQAsCLS41zXPO1KzOEKsrcnbL+eg9hijOESuF5OXrM5lzFz80KKpUKlr2SUXUZQgCYy6ew0KVk9MWlgre5vlNu3ZeHaQu8cL17mXsvfPqpq/iv//sFfOstc/jIj70SP/jAEXzoqy/hp/70ZCCvHyaxmDU5QxgdvAyh34dQucqo1rKHcMtb4HQOyhwz6WC/QKVIjTpjengBoW0LGCHKuHs+hLyREzmkqIxli9DmZX+G0HKDUJUl0ElDa1tRoGuE8R1es/sm06GWjD53bROFqoX7mgRlJDfMOQFhtz5CKSqjRmVUa1AZZVEZhumPibEEkoaGhU1nrbLsWkGo9CEEHC/CThlCIQTOLxdwdIeCMpIT8451RS99z904v1zAv/9fT+KuQ5P4r299OV514yx+8c134KdefwKffuoaPnfq+o6PESaxmDV5YRkdGmwnIDOEikVlDL11htANCLst8GZzKSwXgg4InfPJqBKV0aghQxim7YTuyxByr0q0IJ/tRDKhdqEhkZ8naUyvsn8QcALCagtfvrViDfm0seP5at/EWKiiMo9fWAUA3NvGKPvITAYaYVsfYbseQiUBoV9Uhm0nlMPzcvQgIsznU7i+UUY2m8XV9TKSuoZphT6EALB3onNAuLhVQaFq7VhQRnLYna/OLe68auu9n3kOAPD+7395w5zzzx88jpvnc/i5Tz7dsn1gWInFrMnxYHRoMKYX8ja1x9xphnAml8TyVrAy3fLYqjKEhkaeIqMdwiLaj19Uxg6prJAJBzm2tgCIQu4htAQsW62gDACkdK2lT+BaqYbJABZX+ybSuLIWXkB4ZmELuZSB/RPplvenDB2HpjM427TAar52pcpo0Mb0QGMPYc0SnCFUDM/L0WRv3gnObNvG1fUy9k6klQvKzeVT2CibLcvsgbog39HZYDYhUoaOg1MZnFvaWUB4faOMzz5zHd/3ysM4ONUYrCYNDf/5e+/ElfUyPvSVl3Z0nDCJxazJGcLoYXvCFOpFZdKGDssWqFnNCxwTRECmywJnNpfC0lbAGUJ3caWuh9BnO2GFGxDKtZxGhFIpXDVFRi3yY2TaNmyr9QIgaORn1xIClm0rz3YnjdYB4XqptiOFUcm+iTEsbVVQMcP5+51bKuD4nmzHzOYNe7ZbTzRfu7LMXcWclWoqGeUMoVp4Xo4mc/k0FjYqKJVKuLpewt42m0BBMj/e2Zz+Rc9yIris9LHZLM7tsGT0I1+7AFsIvO2Vh1vef++RaTxwfBp/8sgFT8xs2InFrMnxYHRoXTKq9piphHOZNPcFbZZN5FLdS8BmckkUq1ag5vRbCgUaAFf8w287sQslo9z7Gz3kbvNu9BBadjgZwoTeumR0vVgNJCCU3l1LAVcdtOPcYgHHu+zO37AnixeXCl6ZeSu2KhaSuqYkWEsndFRMC0II9iFkmAHx9/NdXS+3rQoI9Jj5zgHh+eUCdI1woIPfc78cd+crKUzYLzXLxv/8+gW89uY9ONIhUP2+VxzGxZUSvnJ2edBTDZVYzJqcIYwO5DOe8ERlFB8znXCCrnJTH2GhYvZUsjnrqnQFWTYqg0sVEu6AUzLaYDsRoqiMv2Q0kwmmb4AZDsjLEAokE+rkzP00BoR2KD2EtbYlozt/z1INcGlTvdJjqWrh8loJx10l0XbcsCeHimk3iN00X7vFqqms59npIbRRs5w5KxnifBVHeF6OJvP5FApVC6aWwPWNsmdzo/qYAHC9zXz20nIRh6bGAi0DPz6bRbFq4XoXddN2fO7UdSxsVvADDxzp+Lg33L4Xk5kE/ucjFwY6TtjEIiDkeDA6aO4n1skQOqgWlUkZrTOEWz0GhFKlK8iy0YL09FLUQ6hpBMvaHdsJvw8hEy28HmAR3vj6jel3U1RmvVTDZAAZwtlxmSFUHxDKcq3je7pkCF2l0TMdyrAKFUvZBpajMmp5f3fOEDJM/8hs3bNXt1CzBPaFkCGcc4+50CFDeDjAclEA3gbXuaXBykb/9tR1TGUSeOjEXMfHpRM6vuflB/A3z1zzVFuHmVjMmrywjA4yQyi9zIAQfAjbZAi3moyY2yF39IPMEKr09AKcRbTlE5UJ05jenyEsFouhHZdRj/9jZFnhqK+FXTKa1DXULNHQN2LbwukhDEBUZlbBBlM75ILp+GznDOExt6T0vE+oofnadYzrFWUIEzpMW3jCFCwqoxael6PJnJut+8ZLTonjvgn1GcJ82sBYQm9bMnpptYTD08Geh9zgGkRp1LYFvvjCIh68aU9P3yX/9N5DqFkCfzMCFhSxmDU5IIwOXg9hiCWjKcNZxFRq2zOE4x1M6SUyQxik9YQMCFWKylg+URnVSmPNx/b/n4kO/rl4d3oIwxGVAdCQJdwsmxACgfQQeiWjIfQQygXTsS49hNOZJDSCZ2bdikLVVDZfpd0+781yDQBnCBlmEPa62bpnrjkbQWFkCKXdxbUW5Zub5RrWirVtKp47ZX48jbGEPlBAeOrqBpa2qnjtzXt6evyt+8axbyKNh59f6PtYYROLWZPjwejQaEzvBCyqA34pKlNuUvXbKps9lUCpWMCplHAHGgPCsDOE/pLRsTH1O5RMePjLu8PqITQaVEZDsJ1oFRBWnECllw2kbqQTOsZTBhZD6CE8t7iFA5NjGOsyz2gaYSqTbAgIm6/dYtVSZpMjqzg2ys5GWZIzhErheTmayPLNU9ecQCmMgFAet1WG8NKq05N8MEBBGcCZr47NZvHiACWjXzi9CAB4TY8BIRHhoRNz+PKZ5Zbq08NELGZNTjREB7mgFEDddkJ1yWibDGGhYiLXwwIvndCRSxmBlngVqyZShgZD0cJH94nKmPZu+RACmhaLKSo2+D9Gekhj61c2DcNT08sQ+r78pSWCDFx2yux4CouhlIwWuvYPSqazSaz4Nr2ar91Cxexq0TMoco7mDGE48LwcTXIpA7mUgeubVaQMDdNZtab0kvl8umUPoQwIDwWcIQSAY3uyA3kRfuH5RdxxII89bi93Lzx0Yg+2Kia+cX617+OFSSyuatWiI0x41G0nRF1URnHRaLsM4WaPojJA8Ob0vQraDIpG5GVh7dBFZernUCjszDyWGS78nyPTrIVyTMMXEIaxuSGzU/6AUHoGpgIKVGZzSeUqo0KIniwnJNPZJFZ8GcLma7dQ7a3nehDkHL1ecgNCzhAqhefl6CL7CPdNpENbO8+Pp3B9o7LNBuLSqtOrGnSGEABumM3i4kqxLz/XjXIN37iw2nO5qOSbb5xFQic8fHq4y0ZjMWtyD2F0aFUySoo/xa0yhEKInm0nAGAmmww4Q2gpk3AHGhfRVtgloz5RGSZa+Ic0rGlZzv+mLTc31B5PCprULH9A6PwcXECYUi4qs7hZwVbF7Go5IZnJJTv2SRcrljJRGamO+JK748+iMgwzGNIoPgxTeu+Y+TRKNQublUahsYsrJYwldCWZymN7srCFc4xe+dq5FVi2wIM39RcQ5lIG7j86jYefW+z3NEMlFrMmryujQ71kNERRGc+Yvr6TVKpZsAV6KhkFnAVc0CqjqiTcgXqZnWmL0EVlNJ+oTCrVe1kGM/w09BAa6j6/fqSHpm0Lx1NTcblb65JRZ+4IrGQ0l1IuKnN2sTfLCUlzhrD52t1SOGfdsnccAHDy0joALhlVDc/L0UUGgvtDUBiVzLvHvL7eWDZ6abWIQ9NjSjKVh6edee3CSu/Z7scvrMLQCHcfmuz7eA+d2IPnr2/i2nprNdVhIBazpuqSQiY8NK9k1AkKAfUlwXIR588QbpWl7UOvJaOpYFVGFZZfAfXsnC1E+KIyVBeVMUIKGphw8FdrGIa6DLcf3ZchNG31mxvJFr6lKjKE66WaUpGCy2v99e9MZ1NYK9U8MSr/tWtaNiqmrWzOmswksTefxlMcEIYCz8vRxSsZnQwxQ+j24zUbxV9aLQWuMCo5PO287oXl3i1UTl5awy37xgfa2Hvg+AwA4NHzK30/NyyGatYkorcS0bNEVCCis0T0oO++byWi54ioSESfJ6Ijvb+umvNlwqfRh9C5TXWsIhdx/h7CLbe0YbzHBc5sztk9t2zR/cE9UKhYSgPC5r6r3coQcq9KtPB/jMxaOD2EzZsbqqsJW9lOyM2kVEBB8Ox48FY2zVx1A8JeS8dmskkIAawWnSyh/9otuhlSVaIyAHDLvnFcc4UpuGRULTwvR5d6yWiIGUK35LtZafTialFJ/yDgrMkySR3nV3oLCG1b4MmL6wNlBwHg1n15pBPaUAvLDM2sSUTfBuC9AH4EwDiA1wA45943C+DjAN4DYBrAowA+2utrcw9hdPCLyngqo4ozwC0zhJX+MoSzuRRs32Jppzglo+oWV/Kasdy+q92wnVDtF8eEj38uDmt45efJtJySUdXqpqkOojLSL2+neFY2m+rKRq9ulDGdTfa8Gy77fFZaeBEW+pwvB+GEWzYKBJeJZZi4IYOz/SH2EMqs5PXNekC4Xqphs2wqURgFnMqyw9MZXOwxIDy3tIXNiom7Dk4OdLyEruFlByfxGAeEPfGLAH5JCPEPQghbCHFZCHHZve97ATwjhPhTIUQZwC8AuIuIbunlhVkhOXoI+EtG1R7LyxDWtmcI+1EZBRBYH2GxqjZDqDcrM4apMipLRjVCMhmO7DUTDv6PUSKksjN/htCyBXTFH+VWPYRehjDAHkIASoVlrq6V+vIhm8k2znH+a9fzTVU4Z926N+/9zBlCtfC8HF1ecWwa33piBvcemQrtmJmkgfG0gQVfyahKhVHJ4ekMzvdYMvr4hTUAwMsPTw58vHuPTOGZKxsNa8lhYihmTSLSAdwHYA8RnSGiS0T020QkPwm3AzgpHy+EKAA4697e/fW5hzAyeKWLvpJR1SR0DbpGjSWj5T4DwmywC7hCVW2G0AsIpe3ErpSM8sIjavgzhGEFhFJExrRlhjB8H8KgbSfm3J4blV6EV9fL2NdH2diMG6TKDKH/2i1W3Qyh4pJRCfcQqoXn5eiyZzyF93/f3ZjMhDvG8/l0g+BK3ZReTYYQAI7MZHBhpQi7h1aek5fWkEsZOD7bm+pyK+49PAXTFnjS7XUeNqjZ92NXToJoP4DLAL4B4E0AagA+CeBhIcT/RUR/AGBRCPEzvud8GcDvCyE+2OL13gHgHe6vdwB4Wu07YHaRWQBLu30SjDJ4fKMLj2204fGNLjy20YbHN7ocEUK09M0IZYuWiB4G8No2d38ZThAIAL8lhLjqPuc3APwsgP8LwBaAfNPz8gA2W72gEOIDAD7gvs6jQoj7dnL+zPDC4xtteHyjC49ttOHxjS48ttGGxzeehBIQCiEe6vYYIroEwJ+u9P/8DIAf8j02C+AG93aGYRiGYRiGYRhmAIap0P6/A/gJIpojoikAPwngL937/hzAHUT0FiJKA/g5AE8KIZ7bpXNlGIZhGIZhGIYZeYYpIPxlAI8AOA3gWQCPA/hVABBCLAJ4i/v7KoBXAnhrj6/7gcDPlBkmeHyjDY9vdOGxjTY8vtGFxzba8PjGkKEQlWEYhmEYhmEYhmHCZ5gyhAzDMAzDMAzDMEyIcEDIMAzDMAzDMAwTUyIbEBLRNBH9jpJ6CgAACnVJREFUOREViOg8EX3/bp8TMxhElCKiP3DHcZOIniCi7/Dd/61E9BwRFYno80R0ZDfPlxkcIrqJiMpE9GHfbd/vjn2BiD5BRNO7eY5M/xDRW4noWXcMzxLRg+7tfO2OOER0lIg+TUSrRHSNiH6biAz3vruJ6Bvu+H6DiO7e5dNlOkBE7yKiR4moQkQfbLqv7bXqfkf/IRFtuJ+Bd4d+8kxX2o0vET1ARH9LRCtEtEhEf0pE+3z3ExG9l4iW3X/vJSLalTfBKCOyASGA9wOoApgH8DYAv0tEt+/uKTEDYgC4CMfLcgKOP+XH3IXILICPA3gPgGkAjwL46G6dKLNj3g9HXAoA4F6zvwfgB+Bcy0UAv7M7p8YMAhF9G4D3AvgRAOMAXgPgHF+7keF3ACwA2Afgbjjz9DuJKAngkwA+DGAKwIcAfNK9nRlOrgD4FQB/6L+xh2v1FwDcBOAIgH8E4KeJ6NtDOF+mP1qOL5zr8wMAjsIZw004yv+SdwD4bgB3AXgZHO/wf6H2VJmwiaSojOtTuArgDiHEafe2PwZwWQjxM7t6ckwgENGTAH4RwAyAHxZCvMq9PQtgCcDL2ZZktCCitwL4XgCnANwohHg7Ef0nAEeFEN/vPuYGOCrEM0KIzd07W6ZXiOgrAP5ACPEHTbe/A3ztjjxE9CyAfyuE+LT7+68ByAP4MziLyoPCXWgQ0QUA7xBCfGa3zpfpDhH9Cpxx+2H3947XKhFdce//G/f+XwZwkxCiVzV4JkSax7fF/fcA+IIQYtz9/SsAPiiE+ID7+48C+OdCiAdCOmUmBKKaIbwZgCmDQZeTADhDGAGIaB7OGD8DZ0xPyvuEEAUAZ8FjPVIQUR7ALwFoLjVqHt+zcDL/N4d3dsygEJEO4D4Ae4joDBFdcksKx8DXblR4H4C3ElGGiA4A+A4An4Ezjk+Kxl3nJ8HjO4q0vVZd3+h9/vvB661R5zVw1leShvEHj28kiWpAmAOw0XTbOpxyJWaEIaIEgP8B4ENuFiEHZ2z98FiPHr8MJ4t0qel2Ht/RZh5AAsA/AfAgnJLCl8Mp++axjQZfhLM43ABwCU454SfA4xslOo1lzvd7833MiEFELwPwcwD+ne/m5vFfB5DjPsJoEdWAcAtOyYqfPJy6aGZEISINwB/DyRC9y72Zx3rEcYUmXgfgN1vczeM72pTc//+WEOKqEGIJwG8AeCN4bEced07+DJz+siyAWTj9SO8Fj2+U6DSWW77fm+9jRggiuhHAXwP410KIv/fd1Tz+eQBbTdl/ZsSJakB4GoBBRDf5brsLjSlwZoRwd6L+AE7G4S1CiJp71zNwxlY+LgvgBvBYjxIPwWlmv0BE1wD8FIC3ENFj2D6+xwGk4FzjzJAjhFiFkzXyLxzkz3ztjj7TAA4D+G0hREUIsQynb/CNcMbxZU1ZhJeBx3cUaXututf4Vf/94PXWyOGqxn4OwC8LIf646e6G8QePbySJZEDo1rd/HMAvEVGWiL4ZwJvhZJeY0eR3AdwK4E1CiJLv9j8HcAcRvYWI0nBKHZ5kUYqR4gNwFhd3u//+G4C/AvAGOOXBbyKiB91FyC8B+DgLyowU/x3ATxDRnNtv9JMA/hJ87Y48bsb3RQA/TkQGEU0C+CE4vYIPA7AA/CvXlkBWdfzdbpwr0x13DNMAdAA6EaVdC5Fu1+ofAfhZIpoiolsA/HMAH9yFt8B0oN34ur2/fwdnY+e/tXjqHwF4NxEdIKL9AP4teHwjRyQDQpd3AhiDI4f9PwH8uBCCdzRGEHfn6l/ACRauEdGW++9tQohFAG8B8KtwlGVfCYCVzUYIIURRCHFN/oNTnlIWQiy61+y/hBMYLsDpS3nnLp4u0z+/DMdK5DQchdjHAfwqX7uR4XsBfDuARQBnANQA/KQQogpHqv4HAawB+D8BfLd7OzOc/CycMu+fAfB29+ef7eFa/Xk4IjPnAXwBwK+xkuxQ0nJ8AfwYgOMAfsG3vtryPe/3AHwKwFMAnoazYft7YZ44o55I2k4wDMMwDMMwDMMw3YlyhpBhGIZhGIZhGIbpAAeEDMMwDMMwDMMwMYUDQoZhGIZhGIZhmJjCASHDMAzDMAzDMExM4YCQYRiGYRiGYRgmpnBAyDAMwzAMwzAME1M4IGQYhmGYIYOI/jMR/ZsBn/sTRPTegE+JYRiGiSjsQ8gwDMPEAiJ6CcA8AAvAFoDPAHiXEGKr0/PChoj2AHgCwI1CiNIAz0/DMYm/RwixEPDpMQzDMBGDM4QMwzBMnHiTECIH4G4ALwfwH3b3dFrywwA+PUgwCABCiDKAvwbwg0GeFMMwDBNNOCBkGIZhYocQ4hqAz8IJDAEARPQzRHSWiDaJ6BQRfY/vvh8moi8R0X8holUiepGIvsN3/zEi+qL73M8R0fuJ6MO++x8goq8Q0RoRnSSihzqc3ncA+ILvuQ8R0SUi+mkiWiCiq0T03UT0RiI6TUQrRPQfm17jYQD/eLC/DsMwDBMnOCBkGIZhYgcRHYQTeJ3x3XwWwIMAJgD8IoAPE9E+3/2vBPA8gFkA/w+APyAicu/7CICvA5gB8AsAfsB3rAMA/grArwCYBvBTAP7MLQ1txZ3ucfzsBZAGcADAzwH4fQBvB3Cve87vIaJjvsc/C+CuTn8DhmEYhgE4IGQYhmHixSeIaBPARQALAH5e3iGE+FMhxBUhhC2E+CiAFwC8wvfc80KI3xdCWAA+BGAfgHkiOgzgfgA/J4SoCiG+BOAvfM97O5wS0E+7r/23AB4F8MY25zgJYLPpthqAXxVC1AD8CZyg9L8KITaFEM8AOIXGAHATTmDLMAzDMB3hgJBhGIaJE98thBgH8BCAW+AEVgAAIvpBInrCLetcA3CH/34A1+QPQoii+2MOwH4AK77bACfglBwB8E/l67qv/Wo4AWUrVgGMN9227AaiACB7C6/77i+55yIZB7De5vUZhmEYxoMDQoZhGCZ2CCG+AOCDAP4LABDREThlmO8CMCOEmATwNABq8xJ+rgKYJqKM77ZDvp8vAvhjIcSk719WCPF/t3m9JwHc3M/7acGtAE7u8DUYhmGYGMABIcMwDBNX3gfg24joLgBZAALAIgAQ0Y/AyRB2RQhxHk4J6C8QUZKIvgnAm3wP+TCANxHRG4hIJ6K0KxRzsM1LfhrAawd6R3VeC0dplGEYhmE6wgEhwzAME0uEEIsA/ghO798pAL8O4KtwSjHvBPDlPl7ubQC+CcAyHPGYjwKouMe5CODNAP4jnIDzIoB/h/bfwX8E4I1ENNbnWwLg+RC+EU6fI8MwDMN0hI3pGYZhGCZgiOijAJ4TQvx81we3fv5/ArAghHjfAM/9CQCHhBA/PcixGYZhmHjBASHDMAzD7BAiuh/ACoAXAbwewCcAfJMQ4vHdPC+GYRiG6Yax2yfAMAzDMBFgL4CPw/EhvATgxzkYZBiGYUYBzhAyDMMwDMMwDMPEFBaVYRiGYRiGYRiGiSkcEDIMwzAMwzAMw8QUDggZhmEYhmEYhmFiCgeEDMMwDMMwDMMwMYUDQoZhGIZhGIZhmJjCASHDMAzDMAzDMExM+f8BWbh77mzqNCsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "from numpy import log10, finfo\n",
    "\n",
    "\n",
    "# Set the figure size\n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = (15, 10)\n",
    "\n",
    "\n",
    "\n",
    "# Create the line plot\n",
    "\n",
    "plt.plot(range_window, 20.0 * log10(abs(so) / N + finfo(float).eps), '')\n",
    "\n",
    "plt.xlim(0, max(target_range) +  4 * c / bandwidth)\n",
    "\n",
    "plt.ylim(-60, max( 20.0 * log10(abs(so) / N)) + 10)\n",
    "\n",
    "\n",
    "\n",
    "# Set the x and y axis labels\n",
    "\n",
    "plt.xlabel(\"Range (m)\", size=12)\n",
    "\n",
    "plt.ylabel(\"Amplitude (dBsm)\", size=12)\n",
    "\n",
    "\n",
    "\n",
    "# Turn on the grid\n",
    "\n",
    "plt.grid(linestyle=':', linewidth=0.5)\n",
    "\n",
    "\n",
    "\n",
    "# Set the plot title and labels\n",
    "\n",
    "plt.title('Matched Filter Range Profile', size=14)\n",
    "\n",
    "\n",
    "\n",
    "# Set the tick label size\n",
    "\n",
    "plt.tick_params(labelsize=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
